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Unconventionally, they transitioned from Elasticsearch to Postgres FTS and Vector Search.

A key insight was to bring compute closer to storage. This is opposed to more recent database patterns, where storage and compute layers are separated by networked I/O. The Postgres based search ended up being twice as fast by pushing logic and computation down to the data layer instead of pulling data up to the application layer for computation. This approach, combined with Postgres on NVMEs, further improved data fetching performance and reducing latency.