AlloyDB’s agentic database architecture
Entire database engineering careers have been spent on a single question: 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. Aurora offloaded log application to distributed storage nodes, scaling reads across tens of PostgreSQL nodes. 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.
Each of these architectures is inherently constrained by at least one of these three properties: scale, latency, and isolation — and sometimes even two. For instance, architectures built on caches or shared block servers compromise scalability, because I/O inevitably bottlenecks...
Copyright of this story solely belongs to cloud.google.com. To see the full text click HERE
