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r cache & cookies - Computer - Google Account Help Skip to main content Google Account HelpSign inGoogle HelpHelp CenterCommunityGoogle AccountPrivacy PolicyTerms of ServiceSubmit feedback Send feedback on...This help content & informationGeneral Help Center experienceNextHelp CenterCommunityImprove your Google AccountGoogle AccountTroubleshoot issues with Google AccountsClear cache & cookies Clear cache & cookiesWhen you use a browser, like Chrome, it saves some information from websites in its cache and cookies. Clearing them fixes certain problems, like loading or formatting issues on sites.

In Chrome

On your computer, open Chrome.

At the top right, click More Clear browsing data.

Select a time range, like Last hour or All time.

Select the types of information you want to remove.

Click Clear data.

Learn how to change more cookie settings in Chrome. For example, you can delete cookies for a specific site.

In other browsers

If you use Safari, Firefox, or another browser, check its support site for instructions.

What happens after you clear this info

After you clear cache and cookies:

Some settings on sites get deleted. For example, if you were signed in, you’ll need to sign in again.

If you turn sync on in Chrome, you’ll stay signed into the Google Account you’re syncing to in order to delete your data across all your devices.

Some sites can seem slower because content, like images, needs to load again.

How cache & cookies work

Cookies are files created by sites you visit. They make your online experience easier by saving browsing data.

The cache remembers parts of pages, like images, to help them open faster during your next visit.

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How to Clear Your PC's Cache in Windows 10

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How to Clear Your PC's Cache in Windows 10

Marshall Gunnell

Updated Aug 19, 2023

If you need to troubleshoot Windows 10, improve system performance, or just want to clear up some disk space, clear your cache.

Readers like you help support How-To Geek. When you make a purchase using links on our site, we may earn an affiliate commission. Read More.

Read update Here's how to clear your PC's cache after updating to Windows 11.

Quick LinksClear the Temporary Files Cache with Disk Cleanup Clear DNS Cache Clear Windows Store Cache Clear Location Cache

Key Takeaways

Clearing the cache in Windows 10 can help troubleshoot system issues, improve performance, and free up disk space.

Use Disk Cleanup to clear temporary files cache. Select the files you want to delete and click "Clean Up System Files."

Clear DNS cache by opening Command Prompt as an admin and running the command "ipconfig /flushDNS." The Windows Store and location cache can also be cleared.

As with clearing the cache in your browser, clearing the cache in Windows is a good start for troubleshooting system issues, improving system performance, and freeing up disk space. Here's how to clear your cache in Windows 10.

UPDATE: 8/19/2023

Here's how to

clear your PC's cache after updating to Windows 11

Clear the Temporary Files Cache with Disk Cleanup

To clear the temporary files cache, search "Disk Cleanup" in the Start Menu search bar. Select the "Disk Cleanup" app, which will appear in the search results.

Once selected, Disk Cleanup will start calculating how much space you can free up on the operating system drive (C:), or whichever drive you select. On a modern SSD, the window will probably be fast enough that you barely see it. The Disk Cleanup for OS (C:) will now appear. Scroll down and check the box next to "Temporary Files." You can also choose to delete files from other locations, such as "Recycle Bin" or "Downloads."

Once you've selected what you'd like to clear, click "Clean Up System Files."

Once Windows calculates the amount of storage space that will be freed up, you'll be brought to the same page again. This time, select the files and locations a second time that you'd like to delete and then click "OK."

A warning will appear, prompting you to confirm you are sure you want to permanently delete the files. Select "Delete Files."

Disk Cleanup will now clean up unnecessary files on your machine. This process could take several minutes.

Clear DNS Cache

If you want to clear your Windows 10 PC's DNS cache, open Command Prompt as an admin. To do this, click the Start button, then type "Command Prompt" in the search bar. The "Command Prompt" app will appear in the search results. Right-click it and select "Run As Administrator" from the menu, or click "Run as Administrator" on the side.

You can also use PowerShell if you prefer that.

Next, run the following command:

ipconfig /flushDNS

You'll receive a message letting you know you've successfully flushed the DNS Resolver Cache.

Clear Windows Store Cache

To clear the Windows Store cache, open "Run" by pressing Windows+R on your keyboard. The "Run" window will appear. In the text box next to "Open," type WSReset.exe and then click "OK."

Once selected, a black window will very briefly appear. There's nothing you can do here, so just wait a few moments while it clears the cache. You will then see the Windows Store with a blank screen and a loading sign.

Once the window closes, the cache is cleared, and Windows Store will launch. You can close the Windows Store app if you like.

Clear Location Cache

To clear the location cache, click the "Windows" icon in the bottom-left corner of your desktop to open the start menu, From there, select the "Gear" icon to open Windows settings. Alternatively, press Windows+I to open the Settings app.

The "Settings" window will appear. Scroll down and select the "Privacy" option.

You'll now be in the "Privacy" group of the settings. In the left-hand pane, select "Location," found in the "App Permissions" section.

In the next window, scroll down until you find the "Location" group. Here, select "Clear" under the "Location History On This Device" heading.

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What is a cache? And why does clearing it fix things? | Zapier

is a cache? And why does clearing it fix things? | ZapierSkip to contentProductZapier Automation PlatformBring your entire business under one roofPRODUCTSZapsPowerful, do-it-yourself automationTablesDatabases designed for workflowsInterfacesCustom pages to power your workflowsCAPABILITIESApp integrationsExplore 6,000 app integrationsAI featuresAccess our latest AI-powered featuresSecurityEnterprise-grade securityWhat's newCanvasAlphaPlan and map your workflows with AIAI ChatbotBetaCustom no-code chatbots trained on your dataExplore templatesJoin Zapier Early AccessSolutionsBy use caseLead managementSales pipelineMarketing campaignsCustomer supportData managementProject managementTickets and incidentsBy appSalesforceMicrosoft Dynamics CRMHubSpotMarketoSlackMicrosoft TeamsZendeskJira Software CloudJira Service ManagementBy teamMarketingITSalesRevOpsCustomer SupportLeadersBy company sizeStartupsSmall and medium businessesEnterpriseHow Zapier ZapsHow Zapier’s RevOps team automates lead managementHow Zapier Uses AIUsing AI & Zapier in Marketing, Sales, & RevOpsExplore app integrationsJoin Zapier Early AccessResources & SupportBy teamMarketingLeadersITSales operationsLearn moreBlogZapier LearnEvents and webinarsCustomer storiesZapier guidesGet helpHelp CenterCommunityHire an ExpertSupport ServicesContact SupportZapier quick-start guideCreate your first Zap with easeDeveloper resourcesDeveloper PlatformBuild an integrationEmbed an integrationIntegration Partner ProgramDocumentationExplore app integrationsJoin Zapier Early AccessPricingLoadingLoadingHomeProductivityApp tipsApp tips4 min readWhat is a cache? And why does clearing it fix things?By Justin Pot · June 30, 2023It's timeless advice: if a website isn't loading properly, clear your cache. We've all done it. You might have even let out a little "hooray!" when the site started working again. And, if you're like me, you promptly proceeded to not think about the browser cache ever again—until the next thing broke.Get the Zapier blog in your inboxSubscribeBut in the back of your mind, you might be wondering: what the heck is the cache? Why does clearing it fix things? I care about you, and want you to know things, so let's get into it.What is a cache?What does clearing the cache do?Cookies vs. cache: What's the difference?How to clear your browser cacheShould I clear my cache regularly?What is a cache?Cache is the place where your browser stores images, fonts, and a bunch of other technical-sounding things like CSS, HTML, and JavaScript to save bandwidth. Without this feature, your browser would run a lot slower because every site you opened would require re-downloading tons of files. Take, for example, the page you're currently on. There's a Zapier logo at the top-left corner of it. If you go to another Zapier blog post, or to the Zapier homepage, that same logo will be there.It's following you. Your browser could re-download the logo every single time you visit a different page on this site, but that would be wasteful. So, instead, your browser stores the logo, and all sorts of other things, on your computer—in the cache.What does clearing the cache do? Every once in a while, a site will stop working, and clearing the cache will fix it. A coworker of mine, for example, couldn't upload articles to our website, so they cleared the browser cache, and all was right with the world again.Why did this help? To vastly oversimplify things, sometimes there's a difference between the version of a website cached—i.e., stored—on your computer and the version that you're loading from the web. This conflict can lead to weird glitches, and clearing your cache can help when nothing else seems to.In my coworker's case, the backend of the website had recently been updated, which was likely the reason for the conflict.Tip: If you're struggling to sign on to a public Wi-Fi network, the cache might be the problem. Here's how the browser cache comes into play when trying to force open a public Wi-Fi login page—and how to fix it.Cookies vs. cache: What's the difference?In most browsers, the options for clearing the cache and clearing cookies are in the same place—but they're not the same thing.Here's the difference: Cache: This is where your computer stores files downloaded directly from the websites you visit—fonts, images, that kind of thing. The files in your cache aren't that different from the files in the cache of someone else who visits the same websites as you.Cookies: Unlike your cache, cookies store information about you and the things you've done online. If you browse an online store and add a bunch of things to a shopping list, that's saved using a cookie. Cookies also keep track of which site you're logged in to—which is why, if you clear your cookies, you'll need to log back in to all of your accounts. Clearing your cache doesn't affect any of this.Tip: If you want to view the cached version of a website (i.e., a snapshot of the page as it appeared the last time Google robots visited the site), use this simple Google Search trick.How to clear your browser cache Depending on which web browser you're using, the steps to clear your cache might vary. But no matter the browser, it's straightforward to do.How to clear cache on Google ChromeFrom the menu bar of a Google Chrome window, click More (⋮).Click More Tools, and select Clear Browsing Data. You'll be redirected to a pop-up window on Google Chrome's Settings page. Deselect Cookies and other site data (unless you want to clear your cookies), and then click Clear data. How to clear cache on SafariFrom your Mac's menu bar, click History, and then click Clear History.In the pop-up window that appears, click the dropdown beside Clear.Select all history, and then click Clear History.How to clear cache in Microsoft Edge From the menu bar of a Microsoft Edge window, click Settings and more (...).Click Settings, and then select Privacy, search, and services. In the Clear browsing data section, click Choose what to clear. In the pop-up window that appears, select the types of browsing data you want to clear and the desired time range, and then click Clear now. How to clear cache in Firefox For some inexplicable reason, there are two very different ways to clear your cache in Firefox. Here's the most straightforward way. From the menu bar of a Firefox window, click Open application menu, which looks like three lines stacked horizontally (≡), and then click Settings. From the navigation pane, click Privacy & Security. In the Cookies and Site Data section, click Clear Data. In the pop-up window that appears, deselect Cookies and Site Data (unless you want to clear your cookies), and then click Clear. Should I clear my cache regularly?Here's the short answer: in general, I recommend not clearing your cache unless you have a specific reason to.The files in the cache allow the websites you visit most often to load faster, which is a good thing. Plus your browser deletes old files periodically, so it's not like the cache is going to keep growing forever.Sure, the cache is taking up room on your hard drive, and that can be annoying. But the reason you have a hard drive is so you can store things on it. Related reading: Brave browser review: Should you switch?Security behaviors to protect yourself from hackersBlock all website notifications on Chrome with these settings and extensionsThis article was originally published in July 2020. The most recent update, with contributions from Jessica Lau, was in June 2023.

Get productivity tips delivered straight to your inboxSubscribeWe’ll email you 1-3 times per week—and never share your information.Justin PotJustin Pot is a writer and journalist based in Hillsboro, Oregon. He loves technology, people, and nature, not necessarily in that order. Learn more: justinpot.comtagsSecurityTech tipsInternet browsersRelated articlesApp tipsHow to create a report in SalesforceHow to create a report in SalesforceApp tipsHow to copy text from an image or video on WindowsHow to copy text from an image or video on...App tips19 Asana features to start using right now19 Asana features to start using right nowApp tipsWhat is Sora? Everything you need to know about OpenAI's new text-to-video modelWhat is Sora? Everything you need to know...Improve your productivity automatically. Use Zapier to get your apps working together.Sign upSee how Zapier worksPricingHelpDeveloper PlatformPressJobsZapier for CompaniesTemplatesFollow usZapier© 2024 Zapier Inc.Manage cookiesLegalPriv

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1Motivation

2Operation

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2.1Writing policies

2.2Prefetch

3Examples of hardware caches

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3.1CPU cache

3.2GPU cache

3.3DSPs

3.4Translation lookaside buffer

4In-network cache

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4.1Information-centric networking

4.1.1Policies

4.1.1.1Time aware least recently used (TLRU)

4.1.1.2Least frequent recently used (LFRU)

4.1.2Weather forecast

5Software caches

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5.1Disk cache

5.2Web cache

5.3Memoization

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5.6Other caches

6Buffer vs. cache

7See also

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Cache (computing)

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From Wikipedia, the free encyclopedia

Additional storage that enables faster access to main storage

Diagram of a CPU memory cache operation

In computing, a cache (/kæʃ/ ⓘ KASH)[1] is a hardware or software component that stores data so that future requests for that data can be served faster; the data stored in a cache might be the result of an earlier computation or a copy of data stored elsewhere. A cache hit occurs when the requested data can be found in a cache, while a cache miss occurs when it cannot. Cache hits are served by reading data from the cache, which is faster than recomputing a result or reading from a slower data store; thus, the more requests that can be served from the cache, the faster the system performs.[2]

To be cost-effective, caches must be relatively small. Nevertheless, caches are effective in many areas of computing because typical computer applications access data with a high degree of locality of reference. Such access patterns exhibit temporal locality, where data is requested that has been recently requested, and spatial locality, where data is requested that is stored near data that has already been requested.

Motivation[edit]

In memory design, there is an inherent trade-off between capacity and speed because larger capacity implies larger size and thus greater physical distances for signals to travel causing propagation delays. There is also a tradeoff between high-performance technologies such as SRAM and cheaper, easily mass-produced commodities such as DRAM, flash, or hard disks.

The buffering provided by a cache benefits one or both of latency and throughput (bandwidth).

A larger resource incurs a significant latency for access – e.g. it can take hundreds of clock cycles for a modern 4 GHz processor to reach DRAM. This is mitigated by reading large chunks into the cache, in the hope that subsequent reads will be from nearby locations and can be read from the cache. Prediction or explicit prefetching can be used to guess where future reads will come from and make requests ahead of time; if done optimally, the latency is bypassed altogether.

The use of a cache also allows for higher throughput from the underlying resource, by assembling multiple fine-grain transfers into larger, more efficient requests. In the case of DRAM circuits, the additional throughput may be gained by using a wider data bus.

Operation[edit]

Hardware implements cache as a block of memory for temporary storage of data likely to be used again. Central processing units (CPUs), solid-state drives (SSDs) and hard disk drives (HDDs) frequently include hardware-based cache, while web browsers and web servers commonly rely on software caching.

A cache is made up of a pool of entries. Each entry has associated data, which is a copy of the same data in some backing store. Each entry also has a tag, which specifies the identity of the data in the backing store of which the entry is a copy.

When the cache client (a CPU, web browser, operating system) needs to access data presumed to exist in the backing store, it first checks the cache. If an entry can be found with a tag matching that of the desired data, the data in the entry is used instead. This situation is known as a cache hit. For example, a web browser program might check its local cache on disk to see if it has a local copy of the contents of a web page at a particular URL. In this example, the URL is the tag, and the content of the web page is the data. The percentage of accesses that result in cache hits is known as the hit rate or hit ratio of the cache.

The alternative situation, when the cache is checked and found not to contain any entry with the desired tag, is known as a cache miss. This requires a more expensive access of data from the backing store. Once the requested data is retrieved, it is typically copied into the cache, ready for the next access.

During a cache miss, some other previously existing cache entry is typically removed in order to make room for the newly retrieved data. The heuristic used to select the entry to replace is known as the replacement policy. One popular replacement policy, least recently used (LRU), replaces the oldest entry, the entry that was accessed less recently than any other entry. More sophisticated caching algorithms also take into account the frequency of use of entries.

Writing policies[edit]

Main article: Cache coherence

A write-through cache without write allocation

A write-back cache with write allocation

When a system writes data to cache, it must at some point write that data to the backing store as well. The timing of this write is controlled by what is known as the write policy. There are two basic writing approaches:[3]

Write-through: write is done synchronously both to the cache and to the backing store.

Write-back: initially, writing is done only to the cache. The write to the backing store is postponed until the modified content is about to be replaced by another cache block.

A write-back cache is more complex to implement, since it needs to track which of its locations have been written over, and mark them as dirty for later writing to the backing store. The data in these locations are written back to the backing store only when they are evicted from the cache, an effect referred to as a lazy write. For this reason, a read miss in a write-back cache (which requires a block to be replaced by another) will often require two memory accesses to service: one to write the replaced data from the cache back to the store, and then one to retrieve the needed data.

Other policies may also trigger data write-back. The client may make many changes to data in the cache, and then explicitly notify the cache to write back the data.

Since no data is returned to the requester on write operations, a decision needs to be made on write misses, whether or not data would be loaded into the cache. This is defined by these two approaches:

Write allocate (also called fetch on write): data at the missed-write location is loaded to cache, followed by a write-hit operation. In this approach, write misses are similar to read misses.

No-write allocate (also called write-no-allocate or write around): data at the missed-write location is not loaded to cache, and is written directly to the backing store. In this approach, data is loaded into the cache on read misses only.

Both write-through and write-back policies can use either of these write-miss policies, but usually they are paired in this way:[4][5]

A write-back cache uses write allocate, hoping for subsequent writes (or even reads) to the same location, which is now cached.

A write-through cache uses no-write allocate. Here, subsequent writes have no advantage, since they still need to be written directly to the backing store.

Entities other than the cache may change the data in the backing store, in which case the copy in the cache may become out-of-date or stale. Alternatively, when the client updates the data in the cache, copies of those data in other caches will become stale. Communication protocols between the cache managers which keep the data consistent are known as coherency protocols.

Prefetch[edit]

Main article: Cache prefetching

Further information: Memory paging § Page replacement techniques

On a cache read miss, caches with a demand paging policy read the minimum amount from the backing store. For example, demand-paging virtual memory reads one page of virtual memory (often 4 kBytes) from disk into the disk cache in RAM. For example, a typical CPU reads a single L2 cache line of 128 bytes from DRAM into the L2 cache, and a single L1 cache line of 64 bytes from the L2 cache into the L1 cache.

Caches with a prefetch input queue or more general anticipatory paging policy go further—they not only read the data requested, but guess that the next chunk or two of data will soon be required, and so prefetch that data into the cache ahead of time. Anticipatory paging is especially helpful when the backing store has a long latency to read the first chunk and much shorter times to sequentially read the next few chunks, such as disk storage and DRAM.

A few operating systems go further with a loader that always pre-loads the entire executable into RAM.

A few caches go even further, not only pre-loading an entire file, but also starting to load other related files that may soon be requested, such as the page cache associated with a prefetcher or the web cache associated with link prefetching.

Examples of hardware caches[edit]

CPU cache[edit]

Main article: CPU cache

Small memories on or close to the CPU can operate faster than the much larger main memory.[6] Most CPUs since the 1980s have used one or more caches, sometimes in cascaded levels; modern high-end embedded, desktop and server microprocessors may have as many as six types of cache (between levels and functions).[7] Some examples of caches with a specific function are the D-cache, I-cache and the translation lookaside buffer for the memory management unit (MMU).

GPU cache[edit]

Earlier graphics processing units (GPUs) often had limited read-only texture caches, and introduced Morton order swizzled textures to improve 2D cache coherency. Cache misses would drastically affect performance, e.g. if mipmapping was not used. Caching was important to leverage 32-bit (and wider) transfers for texture data that was often as little as 4 bits per pixel, indexed in complex patterns by arbitrary UV coordinates and perspective transformations in inverse texture mapping.

As GPUs advanced (especially with General Purpose GPU compute shaders) they have developed progressively larger and increasingly general caches, including instruction caches for shaders, exhibiting increasingly common functionality with CPU caches. For example, GT200 architecture GPUs did not feature an L2 cache, while the GTX 490 GPU has 768 KB of last-level cache, the GTX TITAN GPU has 1536 KB of last-level cache, and the GTX 980 GPU has 2048 KB of last-level cache. These caches have grown to handle synchronisation primitives between threads and atomic operations, and interface with a CPU-style MMU.

DSPs[edit]

Digital signal processors have similarly generalised over the years. Earlier designs used scratchpad memory fed by direct memory access, but modern DSPs such as Qualcomm Hexagon often include a very similar set of caches to a CPU (e.g. Modified Harvard architecture with shared L2, split L1 I-cache and D-cache).[8]

Translation lookaside buffer[edit]

Main article: Translation lookaside buffer

A memory management unit (MMU) that fetches page table entries from main memory has a specialized cache, used for recording the results of virtual address to physical address translations. This specialized cache is called a translation lookaside buffer (TLB).[9]

In-network cache[edit]

Information-centric networking[edit]

Information-centric networking (ICN) is an approach to evolve the Internet infrastructure away from a host-centric paradigm, based on perpetual connectivity and the end-to-end principle, to a network architecture in which the focal point is identified information (or content or data). Due to the inherent caching capability of the nodes in an ICN, it can be viewed as a loosely connected network of caches, which has unique requirements of caching policies. However, ubiquitous content caching introduces the challenge to content protection against unauthorized access, which requires extra care and solutions.[10]

Unlike proxy servers, in ICN the cache is a network-level solution. Therefore, it has rapidly changing cache states and higher request arrival rates; moreover, smaller cache sizes further impose a different kind of requirements on the content eviction policies. In particular, eviction policies for ICN should be fast and lightweight. Various cache replication and eviction schemes for different ICN architectures and applications have been proposed.

Policies[edit]

Time aware least recently used (TLRU)[edit]

The Time aware Least Recently Used (TLRU)[11] is a variant of LRU designed for the situation where the stored contents in cache have a valid life time. The algorithm is suitable in network cache applications, such as ICN, content delivery networks (CDNs) and distributed networks in general. TLRU introduces a new term: TTU (Time to Use). TTU is a time stamp of a content/page which stipulates the usability time for the content based on the locality of the content and the content publisher announcement. Owing to this locality based time stamp, TTU provides more control to the local administrator to regulate in network storage.

In the TLRU algorithm, when a piece of content arrives, a cache node calculates the local TTU value based on the TTU value assigned by the content publisher. The local TTU value is calculated by using a locally defined function. Once the local TTU value is calculated the replacement of content is performed on a subset of the total content stored in cache node. The TLRU ensures that less popular and small life content should be replaced with the incoming content.

Least frequent recently used (LFRU)[edit]

The Least Frequent Recently Used (LFRU)[12] cache replacement scheme combines the benefits of LFU and LRU schemes. LFRU is suitable for 'in network' cache applications, such as ICN, CDNs and distributed networks in general. In LFRU, the cache is divided into two partitions called privileged and unprivileged partitions. The privileged partition can be defined as a protected partition. If content is highly popular, it is pushed into the privileged partition. Replacement of the privileged partition is done as follows: LFRU evicts content from the unprivileged partition, pushes content from privileged partition to unprivileged partition, and finally inserts new content into the privileged partition. In the above procedure the LRU is used for the privileged partition and an approximated LFU (ALFU) scheme is used for the unprivileged partition, hence the abbreviation LFRU. The basic idea is to filter out the locally popular contents with ALFU scheme and push the popular contents to one of the privileged partition.

Weather forecast[edit]

In 2011, the use of smartphones with weather forecasting options was overly taxing AccuWeather servers; two requests within the same park would generate separate requests. An optimization by edge-servers to truncate the GPS coordinates to fewer decimal places meant that the cached results from the earlier query would be used. The number of to-the-server lookups per day dropped by half.[13]

Software caches[edit]

Disk cache[edit]

Main article: Page cache

While CPU caches are generally managed entirely by hardware, a variety of software manages other caches. The page cache in main memory, which is an example of disk cache, is managed by the operating system kernel.

While the disk buffer, which is an integrated part of the hard disk drive or solid state drive, is sometimes misleadingly referred to as "disk cache", its main functions are write sequencing and read prefetching. Repeated cache hits are relatively rare, due to the small size of the buffer in comparison to the drive's capacity. However, high-end disk controllers often have their own on-board cache of the hard disk drive's data blocks.

Finally, a fast local hard disk drive can also cache information held on even slower data storage devices, such as remote servers (web cache) or local tape drives or optical jukeboxes; such a scheme is the main concept of hierarchical storage management. Also, fast flash-based solid-state drives (SSDs) can be used as caches for slower rotational-media hard disk drives, working together as hybrid drives or solid-state hybrid drives (SSHDs).

Web cache[edit]

Main article: Web cache

Web browsers and web proxy servers employ web caches to store previous responses from web servers, such as web pages and images. Web caches reduce the amount of information that needs to be transmitted across the network, as information previously stored in the cache can often be re-used. This reduces bandwidth and processing requirements of the web server, and helps to improve responsiveness for users of the web.[14]

Web browsers employ a built-in web cache, but some Internet service providers (ISPs) or organizations also use a caching proxy server, which is a web cache that is shared among all users of that network.

Another form of cache is P2P caching, where the files most sought for by peer-to-peer applications are stored in an ISP cache to accelerate P2P transfers. Similarly, decentralised equivalents exist, which allow communities to perform the same task for P2P traffic, for example, Corelli.[15]

Memoization[edit]

Main article: Memoization

A cache can store data that is computed on demand rather than retrieved from a backing store. Memoization is an optimization technique that stores the results of resource-consuming function calls within a lookup table, allowing subsequent calls to reuse the stored results and avoid repeated computation. It is related to the dynamic programming algorithm design methodology, which can also be thought of as a means of caching.

Content delivery network[edit]

Main article: Content delivery network

A content delivery network (CDN) is a network of distributed servers that deliver pages and other Web content to a user, based on the geographic locations of the user, the origin of the web page and the content delivery server.

CDNs began in the late 1990s as a way to speed up the delivery of static content, such as HTML pages, images and videos. By replicating content on multiple servers around the world and delivering it to users based on their location, CDNs can significantly improve the speed and availability of a website or application. When a user requests a piece of content, the CDN will check to see if it has a copy of the content in its cache. If it does, the CDN will deliver the content to the user from the cache.[16]

Cloud storage gateway[edit]

Main article: Cloud storage gateway

A cloud storage gateway, also known as an edge filer, is a hybrid cloud storage device that connects a local network to one or more cloud storage services, typically object storage services such as Amazon S3. It provides a cache for frequently accessed data, providing high speed local access to frequently accessed data in the cloud storage service. Cloud storage gateways also provide additional benefits such as accessing cloud object storage through traditional file serving protocols as well as continued access to cached data during connectivity outages.[17]

Other caches[edit]

The BIND DNS daemon caches a mapping of domain names to IP addresses, as does a resolver library.

Write-through operation is common when operating over unreliable networks (like an Ethernet LAN), because of the enormous complexity of the coherency protocol required between multiple write-back caches when communication is unreliable. For instance, web page caches and client-side network file system caches (like those in NFS or SMB) are typically read-only or write-through specifically to keep the network protocol simple and reliable.

Search engines also frequently make web pages they have indexed available from their cache. For example, Google provides a "Cached" link next to each search result. This can prove useful when web pages from a web server are temporarily or permanently inaccessible.

Database caching can substantially improve the throughput of database applications, for example in the processing of indexes, data dictionaries, and frequently used subsets of data.

A distributed cache[18] uses networked hosts to provide scalability, reliability and performance to the application.[19] The hosts can be co-located or spread over different geographical regions.

Buffer vs. cache[edit]

This section needs additional citations for verification. Please help improve this article by adding citations to reliable sources in this section. Unsourced material may be challenged and removed. (June 2021) (Learn how and when to remove this template message)

The semantics of a "buffer" and a "cache" are not totally different; even so, there are fundamental differences in intent between the process of caching and the process of buffering.

Fundamentally, caching realizes a performance increase for transfers of data that is being repeatedly transferred. While a caching system may realize a performance increase upon the initial (typically write) transfer of a data item, this performance increase is due to buffering occurring within the caching system.

With read caches, a data item must have been fetched from its residing location at least once in order for subsequent reads of the data item to realize a performance increase by virtue of being able to be fetched from the cache's (faster) intermediate storage rather than the data's residing location. With write caches, a performance increase of writing a data item may be realized upon the first write of the data item by virtue of the data item immediately being stored in the cache's intermediate storage, deferring the transfer of the data item to its residing storage at a later stage or else occurring as a background process. Contrary to strict buffering, a caching process must adhere to a (potentially distributed) cache coherency protocol in order to maintain consistency between the cache's intermediate storage and the location where the data resides. Buffering, on the other hand,

reduces the number of transfers for otherwise novel data amongst communicating processes, which amortizes overhead involved for several small transfers over fewer, larger transfers,

provides an intermediary for communicating processes which are incapable of direct transfers amongst each other, or

ensures a minimum data size or representation required by at least one of the communicating processes involved in a transfer.

With typical caching implementations, a data item that is read or written for the first time is effectively being buffered; and in the case of a write, mostly realizing a performance increase for the application from where the write originated. Additionally, the portion of a caching protocol where individual writes are deferred to a batch of writes is a form of buffering. The portion of a caching protocol where individual reads are deferred to a batch of reads is also a form of buffering, although this form may negatively impact the performance of at least the initial reads (even though it may positively impact the performance of the sum of the individual reads). In practice, caching almost always involves some form of buffering, while strict buffering does not involve caching.

A buffer is a temporary memory location that is traditionally used because CPU instructions cannot directly address data stored in peripheral devices. Thus, addressable memory is used as an intermediate stage. Additionally, such a buffer may be feasible when a large block of data is assembled or disassembled (as required by a storage device), or when data may be delivered in a different order than that in which it is produced. Also, a whole buffer of data is usually transferred sequentially (for example to hard disk), so buffering itself sometimes increases transfer performance or reduces the variation or jitter of the transfer's latency as opposed to caching where the intent is to reduce the latency. These benefits are present even if the buffered data are written to the buffer once and read from the buffer once.

A cache also increases transfer performance. A part of the increase similarly comes from the possibility that multiple small transfers will combine into one large block. But the main performance-gain occurs because there is a good chance that the same data will be read from cache multiple times, or that written data will soon be read. A cache's sole purpose is to reduce accesses to the underlying slower storage. Cache is also usually an abstraction layer that is designed to be invisible from the perspective of neighboring layers.

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What Is a Cache? a Complete Guide to Caches and Their Uses

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What is a cache? A complete guide to caches and their important uses on your computer, phone, and other devices

Written by

Dave Johnson

2020-07-07T12:42:00Z

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The cache is an important part of your computer.

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A cache is a special storage space for temporary files that makes a device, browser, or app run faster and more efficiently. After opening an app or website for the first time, a cache stashes files, images, and other pertinent data on your device.Cached data is used to quickly load an app or website for every subsequent visit.Visit Business Insider's Tech Reference library for more stories.

If you've ever troubleshooted something on your computer or cleaned up your browsing history, you've most likely come across advice related to the cache (pronounced "cash"). Most likely, you've been prompted to clear it. But what is a cache, and why would you want to do that? Here's everything you should know about caches and why they're crucial to modern technology.

What is a cache?A cache is a reserved storage location that collects temporary data to help websites, browsers, and apps load faster. Whether it's a computer, laptop or phone, web browser or app, you'll find some variety of a cache. A cache makes it easy to quickly retrieve data, which in turn helps devices run faster. It acts like a memory bank, making it easy to access data locally instead of redownloading it every time you visit a website or open an app.In terms how this affects your day-to-day, there are three main areas where caches play a major role:

Devices and softwareCaches are found in both software and hardware. The CPU, or central processing unit — the core component responsible for processing information from the software in your desktop computer, laptop, smartphone, or tablet — has its own cache. A CPU cache is a small block of memory that's designed to help the CPU easily retrieve frequently used information. It stores data that your device's main memory uses to execute instructions far more quickly than if it had to load every bit of information only when it was requested.

Most computers will let you clear the CPU cache, which can help speed up programs.

Dave Johnson/Business Insider

Web BrowsersEvery web browser, whether it's Microsoft Edge, Chrome, Firefox, or Safari, maintains its own cache. A browser cache stores files needed by your browser to display the web sites it visits. This includes elements like the HTML file that describe the site, along with CSS style sheets, Javascripts, cookies, and images. For example, when you visit Amazon, it downloads all the images associated with product pages you visit, the HTML and other script files needed to render the pages, and personalization information, such as your login information, and the contents of your shopping cart. That's why if you clear your browser cache, retail sites will require you to log back in and rejigger your settings.

AppsApps typically maintain their own cache as well. Like browsers, apps save files and data they deem important so they can quickly reload the information as needed. Every app is different, though, and so the kind of data it caches will vary, but might include images, video thumbnails, search history, and other user preferences.Benefits of cachesFrom a user standpoint, there are three main benefits to caches, including:They make everything run faster. The key benefit of a cache is that it improves the performance of the system. By storing local copies of web site files, for example, your browser only needs to download that information the first time you visit, and can load the local files on subsequent visits. They save data. To help improve performance, apps store recently and frequently used data to the cache. Not only does this allow everything to run faster as previously mentioned, but in some cases it can allow apps to work "offline." For example, if you don't have internet access, an app can rely on cached data to continue to work even without a connection. They store data for later use. There's a lot of efficiency in only downloading files once. If a copy of a file is stored in the cache, then the app doesn't need to waste time, battery power, and other resources downloading it a second time. Instead, the app only needs to download changed or new files.

Downsides of cachesWhile modern software depends heavily on the use of caches, they have some disadvantages as well:They can take up a lot of storage space. In principle, a cache is a small repository of files used by an app. But some caches can grow exceedingly large and limit the free space on your device. Clearing the cache can erase the files and recover a large amount of memory.A corrupted cache can cause the app to behave badly. If there's something wrong with a file stored in the cache, it can cause the app to display data incorrectly, glitch, or even crash. That's why a common remedy for browser issues is clearing the cache. Caches can prevent apps from loading the latest version of a web page or other data. In theory, apps are supposed to only use the cache to display files unchanged since the last visit. That doesn't always work, though, and sometimes the only way to see the latest version of a web site or other info is to clear the cache, so the app is forced to download everything anew.

What does it mean to clear the cache?Given the downsides of cache, it makes practical sense to clear your cache as part of regular maintenance. In addition to corrupted files, if a cache gets too large, or if your computer starts to run low on storage space, these issues can also affect your PC's performance. The solution is to "clear the cache," which deletes the files stored in the cache. If a cache can be cleared by you, the user, the program that owns the cache generally makes that option available somewhere in its settings menu.

Every browser has an easy way to clear its cache.

Dave Johnson/Business Insider

In addition to being able to clear the cache on Windows or iOS, here's how to clear the cache on popular web browsers:Google ChromeSafariMozilla FirefoxWe've also written extensively on how to clear the cache on different devices. Here's how to clear the cache on:TwitterInstagramFacebookSamsung GalaxyiPhones and iPadsChromebooksPS4Xbox OneThe advantages of clearing the cache include freeing up previous storage space on your computer and eliminating any files that might be causing it to misbehave. Unfortunately, clearing the cache also eliminates the files that are designed to make your computer run more efficiently. For example, clearing a browser cache typically means you'll have to log into all your favorite websites all over again, and you'll lose any special customizations or personalization you had there, including the contents of shopping carts or baskets. But if you're experiencing problems with your Mac, PC, or mobile device, clearing the cache is worth it.

Related coverage from Tech Reference:How to clear the Java cache on your Mac or PC to fix web browsing issuesHow to clear the Bluetooth cache on your phone or tablet to fix issues with your connection'Can you clear the cache on a Roku?': No, but here's how to resolve playback issuesHow to clear your Facebook app's cache on an iPhone to help the app run more efficientlyHow to clear the cache on your Xbox One to make your system run faster

Dave Johnson

Freelance Writer

Dave Johnson is a technology journalist who writes about consumer tech and how the industry is transforming the speculative world of science fiction into modern-day real life. Dave grew up in New Jersey before entering the Air Force to operate satellites, teach space operations, and do space launch planning. He then spent eight years as a content lead on the Windows team at Microsoft. As a photographer, Dave has photographed wolves in their natural environment; he's also a scuba instructor and co-host of several podcasts. Dave is the author of more than two dozen books and has contributed to many sites and publications including CNET, Forbes, PC World, How To Geek, and Insider.

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Get Started with Caching

What is Caching?

In computing, a cache is a high-speed data storage layer which stores a subset of data, typically transient in nature, so that future requests for that data are served up faster than is possible by accessing the data’s primary storage location. Caching allows you to efficiently reuse previously retrieved or computed data.

How does Caching work?

The data in a cache is generally stored in fast access hardware such as RAM (Random-access memory) and may also be used in correlation with a software component. A cache's primary purpose is to increase data retrieval performance by reducing the need to access the underlying slower storage layer.

Trading off capacity for speed, a cache typically stores a subset of data transiently, in contrast to databases whose data is usually complete and durable.

Getting Started with Caching: Turbocharging Your Application Workloads

Caching Overview

RAM and In-Memory Engines: Due to the high request rates or IOPS (Input/Output operations per second) supported by RAM and In-Memory engines, caching results in improved data retrieval performance and reduces cost at scale. To support the same scale with traditional databases and disk-based hardware, additional resources would be required. These additional resources drive up cost and still fail to achieve the low latency performance provided by an In-Memory cache.

Applications: Caches can be applied and leveraged throughout various layers of technology including Operating Systems, Networking layers including Content Delivery Networks (CDN) and DNS, web applications, and Databases. You can use caching to significantly reduce latency and improve IOPS for many read-heavy application workloads, such as Q&A portals, gaming, media sharing, and social networking. Cached information can include the results of database queries, computationally intensive calculations, API requests/responses and web artifacts such as HTML, JavaScript, and image files. Compute-intensive workloads that manipulate data sets, such as recommendation engines and high-performance computing simulations also benefit from an In-Memory data layer acting as a cache. In these applications, very large data sets must be accessed in real-time across clusters of machines that can span hundreds of nodes. Due to the speed of the underlying hardware, manipulating this data in a disk-based store is a significant bottleneck for these applications.

Design Patterns: In a distributed computing environment, a dedicated caching layer enables systems and applications to run independently from the cache with their own lifecycles without the risk of affecting the cache. The cache serves as a central layer that can be accessed from disparate systems with its own lifecycle and architectural topology. This is especially relevant in a system where application nodes can be dynamically scaled in and out. If the cache is resident on the same node as the application or systems utilizing it, scaling may affect the integrity of the cache. In addition, when local caches are used, they only benefit the local application consuming the data. In a distributed caching environment, the data can span multiple cache servers and be stored in a central location for the benefit of all the consumers of that data.

Caching Best Practices: When implementing a cache layer, it’s important to understand the validity of the data being cached. A successful cache results in a high hit rate which means the data was present when fetched. A cache miss occurs when the data fetched was not present in the cache. Controls such as TTLs (Time to live) can be applied to expire the data accordingly. Another consideration may be whether or not the cache environment needs to be Highly Available, which can be satisfied by In-Memory engines such as Redis. In some cases, an In-Memory layer can be used as a standalone data storage layer in contrast to caching data from a primary location. In this scenario, it’s important to define an appropriate RTO (Recovery Time Objective--the time it takes to recover from an outage) and RPO (Recovery Point Objective--the last point or transaction captured in the recovery) on the data resident in the In-Memory engine to determine whether or not this is suitable. Design strategies and characteristics of different In-Memory engines can be applied to meet most RTO and RPO requirements.

Layer

Client-Side

DNS

Web

App

Database

Use Case

Accelerate retrieval of web content from websites (browser or device)

Domain to IP Resolution

Accelerate retrieval of web content from web/app servers. Manage Web Sessions (server side)

Accelerate application performance and data access

Reduce latency associated with database query requests

Technologies

HTTP Cache Headers, Browsers

DNS Servers

HTTP Cache Headers, CDNs, Reverse Proxies, Web Accelerators, Key/Value Stores

Key/Value data stores, Local caches

Database buffers, Key/Value data stores

Solutions

Browser Specific

Amazon Route 53

Amazon CloudFront, ElastiCache for Redis, ElastiCache for Memcached, Partner Solutions

Application Frameworks, ElastiCache for Redis, ElastiCache for Memcached, Partner Solutions

ElastiCache for Redis, ElastiCache for Memcached

Caching with Amazon ElastiCache

Amazon ElastiCache is a web service that makes it easy to deploy, operate, and scale an in-memory data store or cache in the cloud. The service improves the performance of web applications by allowing you to retrieve information from fast, managed, in-memory data stores, instead of relying entirely on slower disk-based databases. Learn how you can implement an effective caching strategy with this technical whitepaper on in-memory caching.

Benefits of Caching

Improve Application Performance

Because memory is orders of magnitude faster than disk (magnetic or SSD), reading data from in-memory cache is extremely fast (sub-millisecond). This significantly faster data access improves the overall performance of the application.

Reduce Database Cost

A single cache instance can provide hundreds of thousands of IOPS (Input/output operations per second), potentially replacing a number of database instances, thus driving the total cost down. This is especially significant if the primary database charges per throughput. In those cases the price savings could be dozens of percentage points.

Reduce the Load on the Backend

By redirecting significant parts of the read load from the backend database to the in-memory layer, caching can reduce the load on your database, and protect it from slower performance under load, or even from crashing at times of spikes.

Predictable Performance

A common challenge in modern applications is dealing with times of spikes in application usage. Examples include social apps during the Super Bowl or election day, eCommerce websites during Black Friday, etc. Increased load on the database results in higher latencies to get data, making the overall application performance unpredictable. By utilizing a high throughput in-memory cache this issue can be mitigated.

Eliminate Database Hotspots

In many applications, it is likely that a small subset of data, such as a celebrity profile or popular product, will be accessed more frequently than the rest. This can result in hot spots in your database and may require overprovisioning of database resources based on the throughput requirements for the most frequently used data. Storing common keys in an in-memory cache mitigates the need to overprovision while providing fast and predictable performance for the most commonly accessed data.

Increase Read Throughput (IOPS)

In addition to lower latency, in-memory systems also offer much higher request rates (IOPS) relative to a comparable disk-based database. A single instance used as a distributed side-cache can serve hundreds of thousands of requests per second.

Use Cases & Industries

Use Cases

Industries

Use Cases

Learn about various caching use cases

Database Caching

The performance, both in speed and throughput that your database provides can be the most impactful factor of your application’s overall performance. And despite the fact that many databases today offer relatively good performance, for a lot use cases your applications may require more. Database caching allows you to dramatically increase throughput and lower the data retrieval latency associated with backend databases, which as a result, improves the overall performance of your applications. The cache acts as an adjacent data access layer to your database that your applications can utilize in order to improve performance. A database cache layer can be applied in front of any type of database, including relational and NoSQL databases. Common techniques used to load data into you’re a cache include lazy loading and write-through methods. For more information, click here.

Content Delivery Network (CDN)

When your web traffic is geo-dispersed, it’s not always feasible and certainly not cost effective to replicate your entire infrastructure across the globe. A CDN provides you the ability to utilize its global network of edge locations to deliver a cached copy of web content such as videos, webpages, images and so on to your customers. To reduce response time, the CDN utilizes the nearest edge location to the customer or originating request location in order to reduce the response time. Throughput is dramatically increased given that the web assets are delivered from cache. For dynamic data, many CDNs can be configured to retrieve data from the origin servers.

Amazon CloudFront is a global CDN service that accelerates delivery of your websites, APIs, video content or other web assets. It integrates with other Amazon Web Services products to give developers and businesses an easy way to accelerate content to end users with no minimum usage commitments. To learn more about CDNs, click here.

Domain Name System (DNS) Caching

Every domain request made on the internet essentially queries DNS cache servers in order to resolve the IP address associated with the domain name. DNS caching can occur on many levels including on the OS, via ISPs and DNS servers.

Amazon Route 53 is a highly available and scalable cloud Domain Name System (DNS) web service.

Session Management

HTTP sessions contain the user data exchanged between your site users and your web applications such as login information, shopping cart lists, previously viewed items and so on. Critical to providing great user experiences on your website is managing your HTTP sessions effectively by remembering your user’s preferences and providing rich user context. With modern application architectures, utilizing a centralized session management data store is the ideal solution for a number of reasons including providing, consistent user experiences across all web servers, better session durability when your fleet of web servers is elastic and higher availability when session data is replicated across cache servers.

For more information, click here.

Application Programming Interfaces (APIs)

Today, most web applications are built upon APIs. An API generally is a RESTful web service that can be accessed over HTTP and exposes resources that allow the user to interact with the application. When designing an API, it’s important to consider the expected load on the API, the authorization to it, the effects of version changes on the API consumers and most importantly the API’s ease of use, among other considerations. It’s not always the case that an API needs to instantiate business logic and/or make a backend requests to a database on every request. Sometimes serving a cached result of the API will deliver the most optimal and cost-effective response. This is especially true when you are able to cache the API response to match the rate of change of the underlying data. Say for example, you exposed a product listing API to your users and your product categories only change once per day. Given that the response to a product category request will be identical throughout the day every time a call to your API is made, it would be sufficient to cache your API response for the day. By caching your API response, you eliminate pressure to your infrastructure including your application servers and databases. You also gain from faster response times and deliver a more performant API.

Amazon API Gateway is a fully managed service that makes it easy for developers to create, publish, maintain, monitor, and secure APIs at any scale.

Caching for Hybrid Environments

In a hybrid cloud environment, you may have applications that live in the cloud and require frequent access to an on-premises database. There are many network topologies that can by employed to create connectivity between your cloud and on-premises environment including VPN and Direct Connect. And while latency from the VPC to your on-premises data center may be low, it may be optimal to cache your on-premises data in your cloud environment to speed up overall data retrieval performance.

Web Caching

When delivering web content to your viewers, much of the latency involved with retrieving web assets such as images, html documents, video, etc. can be greatly reduced by caching those artifacts and eliminating disk reads and server load. Various web caching techniques can be employed both on the server and on the client side. Server side web caching typically involves utilizing a web proxy which retains web responses from the web servers it sits in front of, effectively reducing their load and latency. Client side web caching can include browser based caching which retains a cached version of the previously visited web content. For more information on Web Caching, click here.

General Cache

Accessing data from memory is orders of magnitude faster than accessing data from disk or SSD, so leveraging data in cache has a lot of advantages. For many use-cases that do not require transactional data support or disk based durability, using an in-memory key-value store as a standalone database is a great way to build highly performant applications. In addition to speed, application benefits from high throughput at a cost-effective price point. Referenceable data such product groupings, category listings, profile information, and so on are great use cases for a general cache. For more information on general cache, click here.

Integrated Cache

An integrated cache is an in-memory layer that automatically caches frequently accessed data from the origin database. Most commonly, the underlying database will utilize the cache to serve the response to the inbound database request given the data is resident in the cache. This dramatically increases the performance of the database by lowering the request latency and reducing CPU and memory utilization on the database engine. An important characteristic of an integrated cache is that the data cached is consistent with the data stored on disk by the database engine.

Industries

Learn about different industries and the various caching use cases

Mobile

Mobile applications are an incredibly fast growing market segment given the rapid consumer device adoption and the decline in use of traditional computer equipment. Whether it be for games, commercial applications, health applications, and so on, virtually every market segment today has a mobile friendly application. From an application development perspective, building mobile apps is very similar to building any other form of application. You have the same areas of concern, your presentation tier, business tier and data tier. While your screen real estate and development tools are different, delivering a great user experience is a shared goal across all applications. With effective caching strategies, your mobile applications can deliver the performance your users expect, scale massively, and reduce your overall cost.

The AWS Mobile Hub is a console that provides an integrated experience for discovering, configuring, and accessing AWS cloud services for building, testing, and monitoring usage of mobile apps.

Internet of Things (IoT)

The Internet of Things is a concept behind gathering and delivering information from a device and the physical world via device sensors to the internet or application consuming the data. The value of IoT is being able to understand the captured data at near real time intervals which ultimately allows the consuming system and applications the ability to respond rapidly to that data. Take for example, a device that transmits its GPS coordinates. Your IoT application could respond by suggesting points of interest relative to the proximity of those coordinates. Furthermore, if you had stored preferences related to the user of the device, you could fine tune those recommendations tailored to that individual. In this particular example, the speed at which the application can respond to the coordinates is critical to achieving a great user experience. Caching can play an important role here, for example, the points of interest along with the geo coordinates could be stored in a key/value store such as Redis to enable fast retrieval. From an application development perspective, you can essentially code your IoT application to respond to any event given there is a programmatic means to do so. Important considerations to be made when building an IoT architecture include the response time involved with analyzing the ingested data, architecting a solution that can scale N number of devices and delivering an architecture that is cost-effective.

AWS IoT is a managed cloud platform that lets connected devices easily and securely interact with cloud applications and other devices.

Further Reading: Managing IoT and Time Series Data with Amazon ElastiCache for Redis

Advertising Technology

Modern Ad Tech applications are particularly demanding in terms of performance. An example of a significant area of growth in AdTech is real-time bidding (RTB), which is the auction-based approach for transacting digital display ads in real time, at the most granular impression level. RTB was the dominant transaction method in 2015, accounting for 74.0 percent of programmatically purchased advertising, or 11 billion dollars in the US (according to eMarketer Analysis). When building a real-time bidding app, a millisecond can be the difference between submitting the bid on time and it becoming irrelevant. This means that getting the bidding information from the database must be extremely fast. Database caching, which can access bidding details in sub milliseconds, is a great solution for achieving that high performance.

Gaming

Interactivity is a cornerstone requirement for almost any modern game. Nothing frustrates players more than a slow or unresponsive game, and those rarely become successful. The requirement on performance is even more demanding for mobile multiplayer games, where an action that any one player takes needs to be shared with others in real time. Caching plays a crucial role in keeping the game smooth by providing sub-millisecond query response for frequently accessed data. It is also helpful to alleviate hot key issues when the same data is queried multiple times, such as “who are the current top 10 players by score?”

To learn more about developing games on AWS click here.

Media

Media companies often deal with the need to transmit a large amount of static content to their customers with a constantly changing number of readers/viewers. An example is a video streaming service such as Netflix or Amazon Video, which streams a large amount of video content to the viewers. This is a perfect fit for a Content Delivery Network, where data is stored on a globally distributed set of caching servers. Another aspect of media applications is that load tends to be spikey and unpredictable. Imagine a blog on a website that a celebrity just tweeted about, or the website of a Football team during the Super Bowl. Such a large spike of demand to a small subset of content is a challenge to most databases since they are limited in their per-key throughput. Since memory has a much higher throughput than disk, a database cache would resolve the issue by redirecting the reads to the in memory cache.

Ecommerce

Modern eCommerce applications are becoming more sophisticated, offering personalized shopping experience, including real-time recommendations based on a user’s data and shopping history. Those often also include looking at a user’s social network and providing the recommendation based on what her friends liked or purchased. While the amount of data needed to process is increasing, customer’s patience is not. Therefore, keeping the application performing in real-time is not a luxury, but a necessity; a well-executed caching strategy is a critical aspect of the application performance, and could be the difference between an application’s success or failure, between making a sale or losing a customer.

Social Media

Social Media apps have taken the world by storm. Social networks like Facebook, Twitter, Instagram and Snapchat have a vast number of users who consume ever growing amount of content. When a user opens her feed, she expects to see her latest personalized content in near real-time. That is not static content since each user has different friends, images, interests, etc., exacerbating the engineering complexity needs of the underlying platform. Social Media apps are also very prone to spikes in usage around major entertainment, sports, and political events. Such spike resiliency and real-time performance are achieved through multiple layers of caching – including Content Delivery Network for the static content such as background images, session cache for keeping track of a user’s current session data, and database cache for keeping frequently accessed data such as latest news from closest friends and the last few images handy.

Healthcare and Wellness

The healthcare industry is going through a digital revolution, making care both available and accessible to more and more patients around the world. Some applications allow patients to see Doctors for video consultations, and most major providers have apps that allow patients to see their test results and interact with the medical staff. On the wellness side, there is a plethora of applications that range from tracking a user’s specific sensor activity (e.g. FitBit and Jawbone), to comprehensive wellness coaching and data. Given the interactive nature of those apps, the need for fast-performing applications, business, and data tiers must be addressed. With an effective caching strategy you will be able to provide fast performance, reduce the overall infrastructure costs, and scale as your usage grows.

To learn more about building Healthcare apps on AWS click here.

Finance and Financial Technology

The way we consume financial services has evolved dramatically over the recent years. Applications include accessing banking and insurance services, fraud detection, investment services, optimizing capital markets via real-time algorithms, and more. Providing real-time access to a customer’s financial data, allowing him to make transactions such as transferring money, or making payments is challenging. First, similar constraints apply as in other applications where a user wants to interact with the app in near real-time. In addition, financial applications may impose additional requirements such as increased security and fraud detection. An efficient architecture, including multi-layer caching strategy, is critical to achieve the performance expected by users. Based on the application needs, the caching layers would include a session cache for storing a user’s session data, a Content Delivery Network for serving static content, and a database cache for frequently accessed data such as the customer’s 10 most recent purchases.

To learn more about Financial Services apps on AWS click here.

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More Caching Resources

Technical Whitepaper on Database Caching Strategies Using Redis

Technical Whitepaper on In-memory Caching

Amazon CloudFront

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