Episode Details

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Learn how Postgres replaces Elasticsearch, Redis, Kafka, Pinecone, and MongoDB using extensions for AI, vectors, queues, caching, and search.
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This guide shows how modern Postgres extensions can replace large parts of today’s fragmented infrastructure stack. Using pgvector, TimescaleDB, pgmq, PostGIS, pg_cron, and BM25 search, developers can run vector AI search, time-series workloads, caching, queues, geospatial queries, and scheduled jobs directly inside Postgres with fewer services, lower complexity, and unified SQL workflows.