Amazon RDS聽vs聽Compose

Get Advice Icon

Need advice about which tool to choose?Ask the StackShare community!

Amazon RDS
Amazon RDS

4.9K
2.7K
+ 1
754
Compose
Compose

181
95
+ 1
205
Add tool

Amazon RDS vs Compose: What are the differences?

Developers describe Amazon RDS 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. On the other hand, Compose is detailed as "We host databases for busy devs: production-ready, cloud-hosted, open source". Compose makes it easy to spin up multiple open source databases with just one click. Deploy MongoDB for production, take Redis out for a performance test drive, or spin up RethinkDB in development before rolling it out to production.

Amazon RDS belongs to "SQL Database as a Service" category of the tech stack, while Compose can be primarily classified under "MongoDB Hosting".

Some of the features offered by Amazon RDS are:

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

On the other hand, Compose provides the following key features:

  • One click, production-ready, cloud hosted MongoDB, Redis, Elasticsearch, PostgreSQL and RethinkDB, with additional databases in beta.

Every deployment features: database autoscaling based on data size usage - private VLAN, IP whitelisting, SSL, full-stack monitoring, custom alerts - HA and fault tolerance with automatic failover

"Reliable failovers" is the primary reason why developers consider Amazon RDS over the competitors, whereas "Simple to set up" was stated as the key factor in picking Compose.

PedidosYa, New Relic, and Sellsuki are some of the popular companies that use Amazon RDS, whereas Compose is used by StreetHub, Compose, and Gigzolo. Amazon RDS has a broader approval, being mentioned in 1408 company stacks & 509 developers stacks; compared to Compose, which is listed in 82 company stacks and 19 developer stacks.

- No public GitHub repository available -
- No public GitHub repository available -

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.

What is Compose?

Compose makes it easy to spin up multiple open source databases with just one click. Deploy MongoDB for production, take Redis out for a performance test drive, or spin up RethinkDB in development before rolling it out to production.
Get Advice Icon

Need advice about which tool to choose?Ask the StackShare community!

Why do developers choose Amazon RDS?
Why do developers choose Compose?

Sign up to add, upvote and see more prosMake informed product decisions

    Be the first to leave a con
      Be the first to leave a con
      What companies use Amazon RDS?
      What companies use Compose?

      Sign up to get full access to all the companiesMake informed product decisions

      What tools integrate with Amazon RDS?
      What tools integrate with Compose?

      Sign up to get full access to all the tool integrationsMake informed product decisions

      What are some alternatives to Amazon RDS and Compose?
      Amazon Redshift
      It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
      Apache Aurora
      Apache Aurora is a service scheduler that runs on top of Mesos, enabling you to run long-running services that take advantage of Mesos' scalability, fault-tolerance, and resource isolation.
      MySQL
      The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
      Oracle
      Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.
      Heroku Postgres
      Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management.
      See all alternatives
      Decisions about Amazon RDS and Compose
      Tim Specht
      Tim Specht
      鈥嶤o-Founder and CTO at Dubsmash | 13 upvotes 57K 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
      Gregory Koberger
      Gregory Koberger
      Founder | 13 upvotes 55.4K views
      atReadMe.ioReadMe.io
      Compose
      Compose
      MongoLab
      MongoLab
      MongoDB Atlas
      MongoDB Atlas
      PostgreSQL
      PostgreSQL
      MySQL
      MySQL
      MongoDB
      MongoDB

      We went with MongoDB , almost by mistake. I had never used it before, but I knew I wanted the *EAN part of the MEAN stack, so why not go all in. I come from a background of SQL (first MySQL , then PostgreSQL ), so I definitely abused Mongo at first... by trying to turn it into something more relational than it should be. But hey, data is supposed to be relational, so there wasn't really any way to get around that.

      There's a lot I love about MongoDB, and a lot I hate. I still don't know if we made the right decision. We've been able to build much quicker, but we also have had some growing pains. We host our databases on MongoDB Atlas , and I can't say enough good things about it. We had tried MongoLab and Compose before it, and with MongoDB Atlas I finally feel like things are in a good place. I don't know if I'd use it for a one-off small project, but for a large product Atlas has given us a ton more control, stability and trust.

      See more
      Julien DeFrance
      Julien DeFrance
      Principal Software Engineer at Tophatter | 16 upvotes 366.7K 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.

      See more
      Interest over time
      Reviews of Amazon RDS and Compose
      No reviews found
      How developers use Amazon RDS and Compose
      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 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 PSESD
      PSESD uses ComposeCompose

      Hosts primary MongoDB database

      Avatar of GREGORY NICHOLAS
      GREGORY NICHOLAS uses ComposeCompose

      hosts redis, rabbitmq.

      Avatar of Chris Matheson
      Chris Matheson uses ComposeCompose

      data persistence

      How much does Amazon RDS cost?
      How much does Compose cost?
      News about Compose
      More news