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New license management features enable self-hosted customers to manage their CockroachDB license keys in the console UI to track keys and better manage license expirations.
Generic Query Plans is released into GA to optimize query execution by reusing precompiled plans, significantly reducing the CPU overhead associated with parsing and planning repeated queries.
We’ve added new observability features such as work-load level index recommendations, application and database level metrics, and comprehensive hotspot logs to make it easier to track and resolve performance issues at scale, even in multi-tenant setups.
Hot spot observability in external data monitoring tools like Datadog help improve workload stability and performance.
Workload-level index recommendations give high quality index recommendations to holistically optimize performance.
Finer-grained SQL observability by application and database name for simpler troubleshooting.
The CockroachDB cloud offering is being enhanced in many ways.
Physical cluster replication (PCR) is being introduced into Cockroach Cloud as preview. PCR helps customers with two data-center disaster recovery configurations by delivering a solution that supports both a low RPO and RTO. PCR for cloud also supports the ability to offload read-only workloads from the primary cluster to a secondary cluster for better resource utilization.
Vector indexing. In 24.2 we released pgvector support for the vector datatype, which was a good way for customers to begin experimenting with advanced LLM applications. When we introduced pgvector support, we did so for vectors with thousands of dimensions. Now customers are moving their testing along to where performance is important.
To support performant search and discovery we are now introducing vector indexing [link to docs] into Preview based on a protocol we’re calling Cockroach-SPANN (or C-SPANN). C-SPANN is based on Microsoft’s SPANN and SPFRESH research papers which, along with RaBitQ, deliver an indexing method that is small, fully distributed, and easy to update without degrading index quality. We’re very excited about this release as it directly addresses scalability concerns of vector applications for customers with support for indexing billions of vectors.
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