Amazon Aurora vs turbopuffer

Yes, Amazon Aurora offers MySQL and PostgreSQL compatibility with full compatibility to their open-source counterparts, allowing you to migrate existing databases with standard tools.

There is no open source or community edition. Single-tenant and bring-your-own-cloud deployments exist as commercial arrangements, but there is no way to run it independently of the vendor.

Aurora is designed for up to 99.99% single-region uptime and 99.999% multi-region uptime with automatic failover.

Warm queries perform comparably to in-memory search engines. Cold queries, where data is not cached, have a documented p90 around 1,214 ms on a million documents. Write p90 is around 248 ms for a 512 KB upsert because writes go straight to object storage.

Aurora uses serverless, usage-based pricing where you pay only for consumed capacity. Typical pricing ranges from $50-70 per month for minimal setups to $400-600 per month for small production clusters.

Eventually consistent by default, with the vendor reporting that over 99.8% of queries return consistent data. Strong consistency can be requested per query at a latency cost. Large write bursts have a longer visibility delay while indexing catches up.

Yes, Aurora automatically scales to match workload demands without performance degradation, supporting both read and write scaling.

Large numbers of namespaces where most are idle. The architecture makes cold data cheap to keep, which is exactly the shape of a multi-tenant product with a long tail of inactive customers.

Aurora supports up to 15 low-latency read replicas for distributing read traffic across your application.

Up to 128 billion documents and 256 TB per namespace, 500 million documents per shard, 64 MiB per document, 10,752 dense vector dimensions, roughly 10,000 writes per second per namespace and a maximum result set of 10,000.