Amazon RDS logo

Amazon RDS

Set up, operate, and scale a relational database in the cloud.
5.1K
2.8K
+ 1
757

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.
Amazon RDS is a tool in the SQL Database as a Service category of a tech stack.

Who uses Amazon RDS?

Companies
1923 companies reportedly use Amazon RDS in their tech stacks, including Airbnb, Netflix, and 9GAG.

Developers
2973 developers on StackShare have stated that they use Amazon RDS.

Amazon RDS Integrations

Leftronic, Scalyr, Redash, OpsGenie, and Checkmk are some of the popular tools that integrate with Amazon RDS. Here's a list of all 29 tools that integrate with Amazon RDS.

Why developers like Amazon RDS?

Here鈥檚 a list of reasons why companies and developers use Amazon RDS
Amazon RDS Reviews

Here are some stack decisions, common use cases and reviews by companies and developers who chose Amazon RDS in their tech stack.

John-Daniel Trask
John-Daniel Trask
Co-founder & CEO at Raygun | 19 upvotes 79K views
atRaygunRaygun
Amazon S3
Amazon S3
Amazon RDS
Amazon RDS
nginx
nginx
Amazon EC2
Amazon EC2
AWS Elastic Load Balancing (ELB)
AWS Elastic Load Balancing (ELB)
#CloudHosting
#WebServers
#CloudStorage
#LoadBalancerReverseProxy

We chose AWS because, at the time, it was really the only cloud provider to choose from.

We tend to use their basic building blocks (EC2, ELB, Amazon S3, Amazon RDS) rather than vendor specific components like databases and queuing. We deliberately decided to do this to ensure we could provide multi-cloud support or potentially move to another cloud provider if the offering was better for our customers.

We鈥檝e utilized c3.large nodes for both the Node.js deployment and then for the .NET Core deployment. Both sit as backends behind an nginx instance and are managed using scaling groups in Amazon EC2 sitting behind a standard AWS Elastic Load Balancing (ELB).

While we鈥檙e satisfied with AWS, we do review our decision each year and have looked at Azure and Google Cloud offerings.

#CloudHosting #WebServers #CloudStorage #LoadBalancerReverseProxy

See more
Julien DeFrance
Julien DeFrance
Principal Software Engineer at Tophatter | 16 upvotes 483.3K views
atSmartZipSmartZip
Rails
Rails
Rails API
Rails API
AWS Elastic Beanstalk
AWS Elastic Beanstalk
Capistrano
Capistrano
Docker
Docker
Amazon S3
Amazon S3
Amazon RDS
Amazon RDS
MySQL
MySQL
Amazon RDS for Aurora
Amazon RDS for Aurora
Amazon ElastiCache
Amazon ElastiCache
Memcached
Memcached
Amazon CloudFront
Amazon CloudFront
Segment
Segment
Zapier
Zapier
Amazon Redshift
Amazon Redshift
Amazon Quicksight
Amazon Quicksight
Superset
Superset
Elasticsearch
Elasticsearch
Amazon Elasticsearch Service
Amazon Elasticsearch Service
New Relic
New Relic
AWS Lambda
AWS Lambda
Node.js
Node.js
Ruby
Ruby
Amazon DynamoDB
Amazon DynamoDB
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
Ganesa Vijayakumar
Ganesa Vijayakumar
Full Stack Coder | Module Lead | 15 upvotes 475.9K views
Codacy
Codacy
SonarQube
SonarQube
React
React
React Router
React Router
React Native
React Native
JavaScript
JavaScript
jQuery
jQuery
jQuery UI
jQuery UI
jQuery Mobile
jQuery Mobile
Bootstrap
Bootstrap
Java
Java
Node.js
Node.js
MySQL
MySQL
Hibernate
Hibernate
Heroku
Heroku
Amazon S3
Amazon S3
Amazon RDS
Amazon RDS
Solr
Solr
Elasticsearch
Elasticsearch
Amazon Route 53
Amazon Route 53
Microsoft Azure
Microsoft Azure
Amazon EC2 Container Service
Amazon EC2 Container Service
Apache Maven
Apache Maven
Git
Git
Docker
Docker

I'm planning to create a web application and also a mobile application to provide a very good shopping experience to the end customers. Shortly, my application will be aggregate the product details from difference sources and giving a clear picture to the user that when and where to buy that product with best in Quality and cost.

I have planned to develop this in many milestones for adding N number of features and I have picked my first part to complete the core part (aggregate the product details from different sources).

As per my work experience and knowledge, I have chosen the followings stacks to this mission.

UI: I would like to develop this application using React, React Router and React Native since I'm a little bit familiar on this and also most importantly these will help on developing both web and mobile apps. In addition, I'm gonna use the stacks JavaScript, jQuery, jQuery UI, jQuery Mobile, Bootstrap wherever required.

Service: I have planned to use Java as the main business layer language as I have 7+ years of experience on this I believe I can do better work using Java than other languages. In addition, I'm thinking to use the stacks Node.js.

Database and ORM: I'm gonna pick MySQL as DB and Hibernate as ORM since I have a piece of good knowledge and also work experience on this combination.

Search Engine: I need to deal with a large amount of product data and it's in-detailed info to provide enough details to end user at the same time I need to focus on the performance area too. so I have decided to use Solr as a search engine for product search and suggestions. In addition, I'm thinking to replace Solr by Elasticsearch once explored/reviewed enough about Elasticsearch.

Host: As of now, my plan to complete the application with decent features first and deploy it in a free hosting environment like Docker and Heroku and then once it is stable then I have planned to use the AWS products Amazon S3, EC2, Amazon RDS and Amazon Route 53. I'm not sure about Microsoft Azure that what is the specialty in it than Heroku and Amazon EC2 Container Service. Anyhow, I will do explore these once again and pick the best suite one for my requirement once I reached this level.

Build and Repositories: I have decided to choose Apache Maven and Git as these are my favorites and also so popular on respectively build and repositories.

Additional Utilities :) - I would like to choose Codacy for code review as their Startup plan will be very helpful to this application. I'm already experienced with Google CheckStyle and SonarQube even I'm looking something on Codacy.

Happy Coding! Suggestions are welcome! :)

Thanks, Ganesa

See more
John Kodumal
John Kodumal
CTO at LaunchDarkly | 15 upvotes 176.1K views
atLaunchDarklyLaunchDarkly
Amazon RDS
Amazon RDS
PostgreSQL
PostgreSQL
TimescaleDB
TimescaleDB
Patroni
Patroni
Consul
Consul
Amazon ElastiCache
Amazon ElastiCache
Amazon EC2
Amazon EC2
Redis
Redis
Amazon Kinesis
Amazon Kinesis
Kafka
Kafka

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
Jake Stein
Jake Stein
CEO at Stitch | 13 upvotes 100.6K views
atStitchStitch
Go
Go
Amazon RDS
Amazon RDS
Amazon S3
Amazon S3
Amazon Redshift
Amazon Redshift
Amazon EC2
Amazon EC2
AWS OpsWorks
AWS OpsWorks
Kubernetes
Kubernetes
Python
Python
JavaScript
JavaScript
Clojure
Clojure

Stitch is run entirely on AWS. All of our transactional databases are run with Amazon RDS, and we rely on Amazon S3 for data persistence in various stages of our pipeline. Our product integrates with Amazon Redshift as a data destination, and we also use Redshift as an internal data warehouse (powered by Stitch, of course).

The majority of our services run on stateless Amazon EC2 instances that are managed by AWS OpsWorks. We recently introduced Kubernetes into our infrastructure to run the scheduled jobs that execute Singer code to extract data from various sources. Although we tend to be wary of shiny new toys, Kubernetes has proven to be a good fit for this problem, and its stability, strong community and helpful tooling have made it easy for us to incorporate into our operations.

While we continue to be happy with Clojure for our internal services, we felt that its relatively narrow adoption could impede Singer's growth. We chose Python both because it is well suited to the task, and it seems to have reached critical mass among data engineers. All that being said, the Singer spec is language agnostic, and integrations and libraries have been developed in JavaScript, Go, and Clojure.

See more
Tim Specht
Tim Specht
鈥嶤o-Founder and CTO at Dubsmash | 13 upvotes 62.1K views
atDubsmashDubsmash
PostgreSQL
PostgreSQL
Heroku
Heroku
Amazon RDS
Amazon RDS
Amazon DynamoDB
Amazon DynamoDB
Redis
Redis
Amazon RDS for Aurora
Amazon RDS for Aurora
#SqlDatabaseAsAService
#NosqlDatabaseAsAService
#Databases
#PlatformAsAService

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 RDS's Features

  • Pre-configured Parameters
  • Monitoring and Metrics
  • Automatic Software Patching
  • Automated Backups
  • DB Snapshots
  • DB Event Notifications
  • Multi-Availability Zone (Multi-AZ) Deployments
  • Provisioned IOPS
  • Push-Button Scaling
  • Automatic Host Replacement
  • Replication
  • Isolation and Security

Amazon RDS Alternatives & Comparisons

What are some alternatives to Amazon RDS?
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

Amazon RDS's Followers
2759 developers follow Amazon RDS to keep up with related blogs and decisions.
Ryan McCall
Anwin Joselyn
Imran Khalid
Justin Cruz
Fernando Lira
toransahu
Eder Mariano
Tristan Gilford
Prasad Madhbhavikar
ken okamura