Room: The Forum
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We at Instacart have been running a large scale recommender engine in Postgres. We send trained models metadata and features data to Postgres and do inference inside PG. This cluster being a Postgres cluster works with a workload that is a combination of multiple table joins, full text search and personalized ranking via embeddings. The cluster is self hosted, replicas receive WAL shipped by pgbackrest. The applications can survive primary loss by serving stale data and replica loss by banning individual nodes.
The following slides have been made available for this session: