Amazon ElastiCache聽vs聽Amazon RDS

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Amazon ElastiCache vs Amazon RDS: What are the differences?

Developers describe Amazon ElastiCache as "Deploy, operate, and scale an in-memory cache in the cloud". ElastiCache improves the performance of web applications by allowing you to retrieve information from fast, managed, in-memory caches, instead of relying entirely on slower disk-based databases. ElastiCache supports Memcached and Redis. On the other hand, Amazon RDS is detailed as "Set up, operate, and scale a relational database in the cloud". Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call.

Amazon ElastiCache can be classified as a tool in the "Managed Memcache" category, while Amazon RDS is grouped under "SQL Database as a Service".

Some of the features offered by Amazon ElastiCache are:

  • Support for two engines: Memcached and Redis
  • Ease of management via the AWS Management Console. With a few clicks you can configure and launch instances for the engine you wish to use.
  • Compatibility with the specific engine protocol. This means most of the client libraries will work with the respective engines they were built for - no additional changes or tweaking required.

On the other hand, Amazon RDS provides the following key features:

  • Pre-configured Parameters
  • Monitoring and Metrics
  • Automatic Software Patching

"Redis" is the primary reason why developers consider Amazon ElastiCache over the competitors, whereas "Reliable failovers" was stated as the key factor in picking Amazon RDS.

According to the StackShare community, Amazon RDS has a broader approval, being mentioned in 1408 company stacks & 509 developers stacks; compared to Amazon ElastiCache, which is listed in 342 company stacks and 79 developer stacks.

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What is Amazon ElastiCache?

ElastiCache improves the performance of web applications by allowing you to retrieve information from fast, managed, in-memory caches, instead of relying entirely on slower disk-based databases. ElastiCache supports Memcached and Redis.

What is Amazon RDS?

Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call.
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Why do developers choose Amazon ElastiCache?
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      What are some alternatives to Amazon ElastiCache and Amazon RDS?
      Redis
      Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets.
      Elasticsearch
      Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
      Memcached
      Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.
      Azure Redis Cache
      It perfectly complements Azure database services such as Cosmos DB. It provides a cost-effective solution to scale read and write throughput of your data tier. Store and share database query results, session states, static contents, and more using a common cache-aside pattern.
      MemCachier
      MemCachier provides an easy and powerful managed caching solution for all your performance and scalability needs. It works with the ubiquitous memcache protocol so your favourite language and framework already supports it.
      See all alternatives
      Decisions about Amazon ElastiCache and Amazon RDS
      Tim Specht
      Tim Specht
      鈥嶤o-Founder and CTO at Dubsmash | 13 upvotes 49.9K views
      atDubsmashDubsmash
      Amazon RDS for Aurora
      Amazon RDS for Aurora
      Redis
      Redis
      Amazon DynamoDB
      Amazon DynamoDB
      Amazon RDS
      Amazon RDS
      Heroku
      Heroku
      PostgreSQL
      PostgreSQL
      #PlatformAsAService
      #Databases
      #NosqlDatabaseAsAService
      #SqlDatabaseAsAService

      Over the years we have added a wide variety of different storages to our stack including PostgreSQL (some hosted by Heroku, some by Amazon RDS) for storing relational data, Amazon DynamoDB to store non-relational data like recommendations & user connections, or Redis to hold pre-aggregated data to speed up API endpoints.

      Since we started running Postgres ourselves on RDS instead of only using the managed offerings of Heroku, we've gained additional flexibility in scaling our application while reducing costs at the same time.

      We are also heavily testing Amazon RDS for Aurora in its Postgres-compatible version and will also give the new release of Aurora Serverless a try!

      #SqlDatabaseAsAService #NosqlDatabaseAsAService #Databases #PlatformAsAService

      See more
      Amazon ElastiCache
      Amazon ElastiCache
      Amazon Elasticsearch Service
      Amazon Elasticsearch Service
      AWS Elastic Load Balancing (ELB)
      AWS Elastic Load Balancing (ELB)
      Memcached
      Memcached
      Redis
      Redis
      Python
      Python
      AWS Lambda
      AWS Lambda
      Amazon RDS
      Amazon RDS
      Microsoft SQL Server
      Microsoft SQL Server
      MariaDB
      MariaDB
      Amazon RDS for PostgreSQL
      Amazon RDS for PostgreSQL
      Rails
      Rails
      Ruby
      Ruby
      Heroku
      Heroku
      AWS Elastic Beanstalk
      AWS Elastic Beanstalk

      We initially started out with Heroku as our PaaS provider due to a desire to use it by our original developer for our Ruby on Rails application/website at the time. We were finding response times slow, it was painfully slow, sometimes taking 10 seconds to start loading the main page. Moving up to the next "compute" level was going to be very expensive.

      We moved our site over to AWS Elastic Beanstalk , not only did response times on the site practically become instant, our cloud bill for the application was cut in half.

      In database world we are currently using Amazon RDS for PostgreSQL also, we have both MariaDB and Microsoft SQL Server both hosted on Amazon RDS. The plan is to migrate to AWS Aurora Serverless for all 3 of those database systems.

      Additional services we use for our public applications: AWS Lambda, Python, Redis, Memcached, AWS Elastic Load Balancing (ELB), Amazon Elasticsearch Service, Amazon ElastiCache

      See more
      Julien DeFrance
      Julien DeFrance
      Full Stack Engineering Manager at ValiMail | 16 upvotes 264.1K views
      atSmartZipSmartZip
      Amazon DynamoDB
      Amazon DynamoDB
      Ruby
      Ruby
      Node.js
      Node.js
      AWS Lambda
      AWS Lambda
      New Relic
      New Relic
      Amazon Elasticsearch Service
      Amazon Elasticsearch Service
      Elasticsearch
      Elasticsearch
      Superset
      Superset
      Amazon Quicksight
      Amazon Quicksight
      Amazon Redshift
      Amazon Redshift
      Zapier
      Zapier
      Segment
      Segment
      Amazon CloudFront
      Amazon CloudFront
      Memcached
      Memcached
      Amazon ElastiCache
      Amazon ElastiCache
      Amazon RDS for Aurora
      Amazon RDS for Aurora
      MySQL
      MySQL
      Amazon RDS
      Amazon RDS
      Amazon S3
      Amazon S3
      Docker
      Docker
      Capistrano
      Capistrano
      AWS Elastic Beanstalk
      AWS Elastic Beanstalk
      Rails API
      Rails API
      Rails
      Rails
      Algolia
      Algolia

      Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.

      I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.

      For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.

      Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.

      Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.

      Future improvements / technology decisions included:

      Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic

      As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.

      One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.

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      Yonas Beshawred
      Yonas Beshawred
      CEO at StackShare | 9 upvotes 23.1K views
      atStackShareStackShare
      Memcached
      Memcached
      Heroku
      Heroku
      Amazon ElastiCache
      Amazon ElastiCache
      Rails
      Rails
      PostgreSQL
      PostgreSQL
      MemCachier
      MemCachier
      #RailsCaching
      #Caching

      We decided to use MemCachier as our Memcached provider because we were seeing some serious PostgreSQL performance issues with query-heavy pages on the site. We use MemCachier for all Rails caching and pretty aggressively too for the logged out experience (fully cached pages for the most part). We really need to move to Amazon ElastiCache as soon as possible so we can stop paying so much. The only reason we're not moving is because there are some restrictions on the network side due to our main app being hosted on Heroku.

      #Caching #RailsCaching

      See more
      John Kodumal
      John Kodumal
      CTO at LaunchDarkly | 15 upvotes 97.6K views
      atLaunchDarklyLaunchDarkly
      Kafka
      Kafka
      Amazon Kinesis
      Amazon Kinesis
      Redis
      Redis
      Amazon EC2
      Amazon EC2
      Amazon ElastiCache
      Amazon ElastiCache
      Consul
      Consul
      Patroni
      Patroni
      TimescaleDB
      TimescaleDB
      PostgreSQL
      PostgreSQL
      Amazon RDS
      Amazon RDS

      As we've evolved or added additional infrastructure to our stack, we've biased towards managed services. Most new backing stores are Amazon RDS instances now. We do use self-managed PostgreSQL with TimescaleDB for time-series data鈥攖his is made HA with the use of Patroni and Consul.

      We also use managed Amazon ElastiCache instances instead of spinning up Amazon EC2 instances to run Redis workloads, as well as shifting to Amazon Kinesis instead of Kafka.

      See more
      Interest over time
      Reviews of Amazon ElastiCache and Amazon RDS
      No reviews found
      How developers use Amazon ElastiCache and Amazon RDS
      Avatar of Pathwright
      Pathwright uses Amazon RDSAmazon RDS

      While we initially started off running our own Postgres cluster, we evaluated RDS and found it to be an excellent fit for us.

      The failovers, manual scaling, replication, Postgres upgrades, and pretty much everything else has been super smooth and reliable.

      We'll probably need something a little more complex in the future, but RDS performs admirably for now.

      Avatar of AngeloR
      AngeloR uses Amazon RDSAmazon RDS

      We are using RDS for managing PostgreSQL and legacy MSSQL databases.

      Unfortunately while RDS works great for managing the PostgreSQL systems, MSSQL is very much a second class citizen and they don't offer very much capability. Infact, in order to upgrade instance storage for MSSQL we actually have to spin up a new cluster and migrate the data over.

      Avatar of Volkan 脰z莽elik
      Volkan 脰z莽elik uses Amazon ElastiCacheAmazon ElastiCache

      I use a micro elesticache instance as a shared session store between the Node.js clusters of dojo.zerotoherojs.com and nightly.zerotoherojs.com

      Avatar of Wirkn Inc.
      Wirkn Inc. uses Amazon RDSAmazon RDS

      Our PostgreSQL servers, where we keep the bulk of Wirkn data, are hosted on the fantastically easy and reliable AWS RDS platform.

      Avatar of Digital2Go
      Digital2Go uses Amazon RDSAmazon RDS

      We use Aurora for our OLTP database, it provides significant speed increases on top of MySQL without the need to manage it

      Avatar of fadingdust
      fadingdust uses Amazon RDSAmazon RDS

      RDS allows us to replicate the development databases locally as well as making it available to CircleCI.

      Avatar of Cloud Consultant
      Cloud Consultant uses Amazon ElastiCacheAmazon ElastiCache

      Audit the ElastiCache configurations for best practices and standards.

      Avatar of Binded
      Binded uses Amazon ElastiCacheAmazon ElastiCache

      We use ElastiCache to run Redis, which we use as a queue through Kue.

      Avatar of Instacart
      Instacart uses Amazon ElastiCacheAmazon ElastiCache

      We use Elasticache. Both Redis and Memchached.

      Avatar of B霉i Thanh
      B霉i Thanh uses Amazon ElastiCacheAmazon ElastiCache
      • Redis cluster for cache and session storage
      How much does Amazon ElastiCache cost?
      How much does Amazon RDS cost?