Updated 04/2022 to reflect product changes.
Amazon Relational Database Service (Amazon RDS) simplifies the setup, operation, and scaling of relational databases in the cloud. It offers cost-effective and resizable capacity while automating tedious administrative tasks such as hardware provisioning, database setup, patching, and backups. This allows developers to concentrate on their applications, ensuring they achieve fast performance, high availability, security, and compatibility.
Transitioning from self-managed databases to managed services has become increasingly common, and we are continually enhancing Amazon RDS’s capabilities. The year 2019 was particularly eventful, so let’s recap the key features launched across various database engines.
Amazon RDS debuted in October 2009, starting with Amazon RDS for MySQL, and has since expanded to include seven database engine options: Amazon Aurora MySQL, Amazon Aurora PostgreSQL, PostgreSQL, MySQL, MariaDB, Oracle Database, and Microsoft SQL Server.
In 2019, we introduced over 100 new features across all Amazon RDS and Aurora database engines. For a quick reference, check out the 2018 recap and the 2017 recap. Below, we’ll delve into each database engine and highlight the most impactful releases for your database strategy and operations. We will also list all features launched in 2019, sorted for your convenience:
- New instance types, Regions, and versions – Offering diverse deployment options
- Manageability – Streamlining database management and providing expert recommendations
- Developer productivity – Allowing developers to concentrate on business-critical tasks
- Performance – Enhancing database performance and scalability to meet application demands
- Availability/Disaster Recovery – Deploying highly available databases across Availability Zones and AWS Regions
- Security – Ensuring secure database operations
Noteworthy Feature Launches of 2019
Amazon Aurora MySQL
In 2019, Aurora Global Database, initially introduced at re:Invent 2018, expanded to support multiple Regions for enhanced disaster recovery and faster global reads. The feature now accommodates up to five secondary Regions and MySQL 5.7, along with in-place upgrades from single-region databases. Additionally, we launched Aurora Multi-Master, which boosts availability by enabling multiple read/write instances across various Availability Zones, and Aurora Machine Learning, allowing you to integrate machine learning predictions directly within your SQL queries. For more on this, you can read another blog post here.
Amazon Aurora PostgreSQL
For Aurora PostgreSQL, we introduced Serverless support, which automatically manages database startup, shutdown, and scaling according to application requirements. This feature is particularly beneficial for infrequently used applications, new projects, variable workloads, and multi-tenant applications. Other significant additions include support for Logical Replication using PostgreSQL replication slots, detailed auditing through Database Activity Streams, and improved S3 data import capabilities. Furthermore, we added support for PostgreSQL version 11 and achieved FedRAMP HIGH compliance.
Amazon RDS for Oracle
We enhanced availability and disaster recovery by launching In-Region and Cross-Region Read Replicas with Oracle Active Data Guard. This allows the creation of up to five fully managed Oracle Active Data Guard standby databases for read scaling and offloading lengthy analytical queries. We also simplified migrations to RDS for Oracle using Amazon S3 for data ingress and egress, making it easier to transfer files securely.
Amazon RDS for SQL Server
We increased the maximum number of databases per instance from 30 to 100, enabling greater consolidation and cost savings. In addition, we improved migration efficiency by allowing Native Differential and Log Backups alongside Full Native Backups, reducing downtime to as little as five minutes. Lastly, we launched Always On Availability Groups for SQL Server 2017 Enterprise Edition, introducing the Always On Listener Endpoint for quicker failovers.
Cross-Engine Releases
For easier single sign-on, Microsoft Active Directory (AD) integration is now available via AWS Managed Active Directory Service for Amazon RDS PostgreSQL, RDS Oracle, and RDS MySQL. This allows the use of the same AD across different VPCs within the same AWS Region and supports joining instances to a shared Active Directory domain across different accounts.
Finally, we announced the public preview of Amazon RDS Proxy for Amazon RDS MySQL and Aurora MySQL, which enhances database efficiency by pooling and sharing database connections, thereby boosting application scalability. In the event of a database failover, RDS Proxy seamlessly connects to a standby database instance while maintaining connections from the application, reducing failover times by up to 66% for Multi-AZ databases. Credentials management is streamlined through AWS Secrets Manager and AWS Identity and Access Management (IAM), eliminating the need to hardcode credentials in application code. Support for Amazon RDS for PostgreSQL and Aurora with PostgreSQL compatibility will be available soon, and you can learn more from those who are an authority on this topic here.
Features by Database Engine
Amazon Aurora MySQL
- Launched new instance types, including T3 and R5 families
- Support for R5.8xl, R5.16xl, and R5.24xl instances
- Available in the AWS Americas (São Paulo) Region
- Expansion of Aurora Global Database to 14 AWS Regions
Manageability
- Key 2019 launch: Multi-Master is generally available, enhancing overall performance
For those looking to delve deeper into onboarding new hires during the pandemic, this is an excellent resource here.
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