A new, no-compromises database architecture for the agentic era

The useful part

How do you scale an OLTP workload without compromising the system of record that owns the data? Exadata answered the question by offloading queries into a scale-out storage tier beneath the database, removing the network as the bottleneck. Azure SQL Hyperscale did it with shared block servers, scaling out to tens of read replicas.

How it works

• Meanwhile, emerging architectures persist data in traditional object storage with a provisioned cache tier in front, recovering latency for hot data but leaving a high-latency tail on every cache miss.
• They also sacrifice isolation, as production workloads get throttled whenever replica traffic spikes.
• However, in the agentic era, these compromises are no longer acceptable.
• Aurora offloaded log application to distributed storage nodes, scaling reads across tens of PostgreSQL nodes.
• Each of these architectures is inherently constrained by at least one of these three properties: scale, latency, and isolation — and sometimes even two.

What to take from it

For instance, architectures built on shared block servers compromise scalability, because I/O inevitably bottlenecks on the block server.