Aurora DSQL is a new "serverless" database system from Amazon Web Services.
"Aurora DSQL is a new serverless SQL database, optimized for transaction processing, and designed for the cloud. DSQL is designed to scale up and down to serve workloads of nearly any size, from your hobby project to your largest enterprise application. All the SQL stuff you expect is there: transactions, schemas, indexes, joins, and so on, all with strong consistency and isolation."
If you're wondering what they mean by "serverless":
"Here, we mean that you create a cluster in the AWS console (or API or CLI), and that cluster will include an endpoint. You connect your PostgreSQL client to that endpoint. That's all you have to do: management, scalability, patching, fault tolerance, durability, etc are all built right in. You never have to worry about infrastructure."
If you're wondering about the technology behind it, they say:
"At the same time, a few pieces of technology were coming together. One was a set of new virtualization capabilities, including Caspian (which can dynamically and securely scale the resources allocated to a virtual machine up and down), Firecracker (a lightweight VMM for fast-scaling applications), and the VM snapshotting technology we were using to build Lambda Snapstart."
"The second was EC2 time sync, which brings microsecond-accurate time to EC2 instances around the globe. High-quality physical time is hugely useful for all kinds of distributed system problems. Most interestingly, it unlocks ways to avoid coordination within distributed systems, offering better scalability and better performance."
"The third was Journal, the distributed transaction log we'd used to build critical parts of multiple AWS services (such as MemoryDB, the Valkey compatible durable in-memory database). Having a reliable, proven, primitive that offers atomicity, durability, and replication between both availability zones and regions simplifies a lot of things about building a database system (after all, Atomicity and Durability are half of ACID)."
"The fourth was AWS's strong formal methods and automated reasoning tool set. Formal methods allow us to explore the space of design and implementation choices quickly, and also helps us build reliable and dependable distributed system implementations. Distributed databases, and especially fast distributed transactions, are a famously hard design problem, with tons of interesting trade-offs, lots of subtle traps, and a need for a strong correctness argument. Formal methods allowed us to move faster and think bigger about what we wanted to build."