Amazon Aurora

It's suited where you have enterprise applications and integrate open-source databases without requiring a license.

We used MySQL from different cloud services, but it was fluctuating in another country (Pakistan). Then, we tested out AWS RDS Aurora, and the connection was fluctuating. It was highly available.

The support as a whole cannot be applied to just Aurora, but I must say that the response to our tickets from the AWS side was a bit anemic. Despite that, there is plenty of documentation and forum articles that should make anybody self-serviced. Again, let me stress this out - the product (in either MySQL or Postgres form) was used by many people and thus now well understood, explained and there are plenty of books and other material available. This is not the case that we encountered with NoSQL.

Aurora is great for situations where databases require autoscaling and need high availability. For example, high traffic websites running on an autoscaling compute layer can benefit by being connected to a datastore that can scale along with them. Also any scenario that requires fault tolerance can benefit greatly from Aurora. Knowing that your DB can heal itself (to the best of its ability) can give developers and engineers confidence that their application will handle adverse scenarios in the event of failure conditions. Given the premium of running DBs with Aurora, I would not recommend using it for development environments. Given that Aurora is compatible with most common DB software, development environments can use cheaper, smaller RDS instances. When it comes time for deploying into a production environment, no changes would be needed.

AWS has been top notch in providing support for Aurora and RDS as a whole. For the most part, there is rarely ever a need to request support for our database deployments. The only interactions I can think of off hand are asking for increases in the number of instances we can deploy.

Aurora is easy to deploy and operate from the AWS console, the command line, and with Infrastructure as Code tools like Cloudformation and Terraform. Integrating the endpoints into an application is easy because from the outside, the Aurora clusters look just like any other open source database. I have also seen benefit from using the instances within the cluster as distinct read and write endpoints allowing for further customization in our applications.

For workloads that already use, or plan on using, MySQL or PostgreSQL, Aurora is our new go-to favorite deployment option for projects on AWS. The best use cases for Aurora will be substantial workloads that are well-suited to the simple scaling controls (both from an instance type perspective, as well as storage perspective), and will benefit from Aurora's simple, very low latency read replicas. Aurora is extremely fault tolerant and has improved self-healing ability.

Many places where Aurora is well suited:

• If you are trying to build a serverless backend.
• Amazon hosted relational database service (RDS). So we do not have to manage the database maintenance.
• Backup and archival can be done to AWS S3, which is very convenient.
• It provides high performance and scalability.
• It's very secure. You could use AWS Key management service (KMS) to encrypt and store data on AWS Aurora.