Amazon has unveiled the general availability of Amazon Aurora DSQL, a cutting-edge database solution that is both PostgreSQL-compatible and serverless. This innovative managed service is crafted to deliver active-active high availability alongside multi-region strong consistency, catering to the needs of modern applications.
Technical Innovations in Aurora DSQL
Initially previewed during the recent re:Invent keynote, Aurora DSQL is engineered for scenarios that require global scalability, resilience, and unwavering performance. Channy Yun, lead blogger at AWS, elaborates on the architecture:
Unlike most traditional databases, Aurora DSQL is disaggregated into multiple independent components such as a query processor, adjudicator, journal, and crossbar. These components have high cohesion, communicate through well-specified APIs, and scale independently based on your workloads.
Within a single region, Aurora DSQL boasts an impressive 99.99% availability rate, while its multi-region deployments are designed to achieve an even higher 99.999% availability. The system is adept at automatic recovery from failures, with two regional endpoints acting as peers to facilitate concurrent operations while ensuring strong consistency. The third region serves as a log-only witness, further enhancing overall availability. Yun notes:
Aurora DSQL is an ideal choice to support applications using microservices and event-driven architectures. It’s also perfect for multi-tenant software as a service (SaaS) applications and data-driven services like payment processing, gaming platforms, and social media applications.
In multi-region cluster deployments, all read and write operations maintain consistency and durability across regional endpoints, presenting a unified logical database. This configuration allows applications to seamlessly read from and write to any location.
Source: AWS blog
Luc van Donkersgoed, Principal Engineer at PostNL and AWS Hero, expresses his enthusiasm, stating:
This is the biggest product launch in years, rivaling Lambda and DynamoDB in its potential.
In a detailed article titled “Just make it scale: An Aurora DSQL story,” senior principal engineers Niko Matsakis and Marc Bowes share their technical insights on utilizing Rust in the development of DSQL. They emphasize:
The goal with Aurora DSQL’s design is to break up the database into bite-sized chunks with clear interfaces and explicit contracts. Each component follows the Unix mantra—do one thing, and do it well—but working together they are able to offer all the features users expect from a database (transactions, durability, queries, isolation, consistency, recovery, concurrency, performance, logging, and so on).
Source: All Things Distributed
Marc Brooker, VP and distinguished engineer at AWS, has previously published an extensive series of posts about the DSQL design and implementation, providing a deeper understanding of the service’s architecture.
While the community response has generally been positive, some users have expressed confusion regarding the new normalized billing unit known as the Distributed Processing Unit (DPU) and its comparison to existing alternatives. There are also concerns about compatibility. AWS assures users that “Aurora DSQL and PostgreSQL return identical results for all SQL queries,” and the database supports essential relational features such as ACID transactions, secondary indexes, joins, inserts, and updates. However, the documentation includes a thorough list of SQL feature compatibility, highlighting unsupported PostgreSQL features. User sh1boleth comments:
I think for orgs that already use full-fledged MySQL/Postgres this won’t offer many benefits other than ease of use and infinite scaling; however, for orgs that use DynamoDB and feel restricted with its modeling and lack of relations (and don’t want to handle the headache that is Single Table), this is a nice middle ground between a full relational DB vs NoSQL.
With the general availability launch, Aurora DSQL has expanded its support to additional regions in Europe and Asia Pacific, and introduced features such as PostgreSQL views, CloudFormation, KMS customer-managed keys, and AWS Backup. Additionally, a Model Context Protocol (MCP) server has been announced for AI application workloads, which translates human-readable questions and commands into structured PostgreSQL-compatible SQL.
As with other managed AWS services, a free tier is available, covering 100,000 DPUs and 1 GB-month of storage each month.
Amazon Aurora DSQL Goes GA: Distributed, PostgreSQL-Compatible Serverless Database
Amazon has unveiled the general availability of Amazon Aurora DSQL, a cutting-edge database solution that is both PostgreSQL-compatible and serverless. This innovative managed service is crafted to deliver active-active high availability alongside multi-region strong consistency, catering to the needs of modern applications.
Technical Innovations in Aurora DSQL
Initially previewed during the recent re:Invent keynote, Aurora DSQL is engineered for scenarios that require global scalability, resilience, and unwavering performance. Channy Yun, lead blogger at AWS, elaborates on the architecture:
Within a single region, Aurora DSQL boasts an impressive 99.99% availability rate, while its multi-region deployments are designed to achieve an even higher 99.999% availability. The system is adept at automatic recovery from failures, with two regional endpoints acting as peers to facilitate concurrent operations while ensuring strong consistency. The third region serves as a log-only witness, further enhancing overall availability. Yun notes:
In multi-region cluster deployments, all read and write operations maintain consistency and durability across regional endpoints, presenting a unified logical database. This configuration allows applications to seamlessly read from and write to any location.
Source: AWS blog
Luc van Donkersgoed, Principal Engineer at PostNL and AWS Hero, expresses his enthusiasm, stating:
In a detailed article titled “Just make it scale: An Aurora DSQL story,” senior principal engineers Niko Matsakis and Marc Bowes share their technical insights on utilizing Rust in the development of DSQL. They emphasize:
Source: All Things Distributed
Marc Brooker, VP and distinguished engineer at AWS, has previously published an extensive series of posts about the DSQL design and implementation, providing a deeper understanding of the service’s architecture.
While the community response has generally been positive, some users have expressed confusion regarding the new normalized billing unit known as the Distributed Processing Unit (DPU) and its comparison to existing alternatives. There are also concerns about compatibility. AWS assures users that “Aurora DSQL and PostgreSQL return identical results for all SQL queries,” and the database supports essential relational features such as ACID transactions, secondary indexes, joins, inserts, and updates. However, the documentation includes a thorough list of SQL feature compatibility, highlighting unsupported PostgreSQL features. User sh1boleth comments:
With the general availability launch, Aurora DSQL has expanded its support to additional regions in Europe and Asia Pacific, and introduced features such as PostgreSQL views, CloudFormation, KMS customer-managed keys, and AWS Backup. Additionally, a Model Context Protocol (MCP) server has been announced for AI application workloads, which translates human-readable questions and commands into structured PostgreSQL-compatible SQL.
As with other managed AWS services, a free tier is available, covering 100,000 DPUs and 1 GB-month of storage each month.