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Amazon RDS for Aurora

MySQL and PostgreSQL compatible relational database with several times better performance
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What is Amazon RDS for Aurora?

Amazon Aurora is a MySQL-compatible, relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora provides up to five times better performance than MySQL at a price point one tenth that of a commercial database while delivering similar performance and availability.
Amazon RDS for Aurora is a tool in the SQL Database as a Service category of a tech stack.

Who uses Amazon RDS for Aurora?

Companies
215 companies reportedly use Amazon RDS for Aurora in their tech stacks, including StackShare, Delivery Hero, and medium.com.

Developers
239 developers on StackShare have stated that they use Amazon RDS for Aurora.

Amazon RDS for Aurora Integrations

MySQL, PostgreSQL, AWS Glue, Amazon Quicksight, and Stitch are some of the popular tools that integrate with Amazon RDS for Aurora. Here's a list of all 13 tools that integrate with Amazon RDS for Aurora.
Public Decisions about Amazon RDS for Aurora

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

Julien DeFrance
Julien DeFrance
Principal Software Engineer at Tophatter | 16 upvotes 路 1.8M views

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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Tim Specht
Tim Specht
鈥嶤o-Founder and CTO at Dubsmash | 13 upvotes 路 98.8K views

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

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Pedro Arnal Puente
Pedro Arnal Puente
CTO at La Cupula Music SL | 8 upvotes 路 359.6K views

Our base infrastructure is composed of Debian based servers running in Amazon EC2 , asset storage with Amazon S3 , and Amazon RDS for Aurora and Redis under Amazon ElastiCache for data storage.

We are starting to work in automated provisioning and management with Terraform , Packer , and Ansible .

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Chris McFadden
Chris McFadden
VP, Engineering at SparkPost | 5 upvotes 路 38.9K views

We migrated most of our APIs last year from using our self managed Cassandra cluster to a mix of Amazon DynamoDB and Amazon RDS for Aurora. This has reduced the operational overhead for our team and greatly improved the overall reliability of our service. The new dynamic capacity in DynamoDB has been super helpful for handling bursty traffic.

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Lukas Bergamo
Lukas Bergamo
CEO & Founder at 鹿OnePlace | 5 upvotes 路 10.6K views

Our team finalized the migration of the systemic structure that previously remained monolithic, now using micro services.

We have adopted as NodeJs services and for some WCF services with Asp.Net Core.

Now each service has its separate lifecycle and with the help of the containers we increase the scalability in 40% of calls. Node.js Docker Amazon EC2 Container Service Amazon RDS for Aurora

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Roman Labunsky
Roman Labunsky
Head of Engineering at datree.io | 3 upvotes 路 8.9K views
Shared insights
on
Amazon RDS for AuroraAmazon RDS for Aurora
at

We use Amazon RDS for Aurora because we needed a cloud level scalable solution for database management. We wanted to use a modern database engine that's suitable for the cloud era and also benefit from using SQL and a structured database.

We never wanted to manage the DB infrastructure ourselves so our choice was between Aurora and simply RDS. We chose Aurora because of superior performance and the ease of scaling storage and instances.

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Amazon RDS for Aurora's Features

  • High Throughput with Low Jitter
  • Push-button Compute Scaling
  • Storage Auto-scaling
  • Amazon Aurora Replicas
  • Instance Monitoring and Repair
  • Fault-tolerant and Self-healing Storage
  • Automatic, Continuous, Incremental Backups and Point-in-time Restore
  • Database Snapshots
  • Resource-level Permissions
  • Easy Migration
  • Monitoring and Metrics

Amazon RDS for Aurora Alternatives & Comparisons

What are some alternatives to Amazon RDS for Aurora?
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.
Google Cloud SQL
MySQL databases deployed in the cloud without a fuss. Google Cloud Platform provides you with powerful databases that run fast, don鈥檛 run out of space and give your application the redundant, reliable storage it needs.
Azure SQL Database
It is the intelligent, scalable, cloud database service that provides the broadest SQL Server engine compatibility and up to a 212% return on investment. It is a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software.
Books
It is an immutable double-entry accounting database service. It supports many clients and businesses at global scale, leaning on Google Cloud Spanner and Google Kubernetes Engine to make that possible.
DigitalOcean Managed Databases
Build apps and store data in minutes with easy access to one or more databases and sleep better knowing your data is backed up and optimized.
See all alternatives

Amazon RDS for Aurora's Followers
412 developers follow Amazon RDS for Aurora to keep up with related blogs and decisions.
D Vera
Kevin Collins
Mervin Lavin
Catalin Netcu
Harish Agarwal
Muhammad Hassan
Luka Djurisic
Patrick McGrath
Ahmed Sherif
Manu Aggarwal