Raja Rao DV - Blog | Tiger Data

Elasticsearch's Hybrid Search, Now in Postgres (BM25 + Vector + RRF)

PostgreSQL

Elasticsearch's Hybrid Search, Now in Postgres (BM25 + Vector + RRF)

Build hybrid search in Postgres with pg_textsearch BM25, pgvectorscale vectors, and RRF. Auto-sync embeddings with pgai—no Elasticsearch pipeline needed.

By Raja Rao DV

February 9th, 2026

It’s 2026, Just Use Postgres

PostgreSQL

TimescaleDB

It’s 2026, Just Use Postgres

Stop managing multiple databases. Postgres extensions replace Elasticsearch, Pinecone, Redis, MongoDB, and InfluxDB with BM25, vectors, JSONB, and time-series in one database.

By Raja Rao DV

February 2nd, 2026

10 Elasticsearch Production Issues (and How Postgres Avoids Them)

PostgreSQL

10 Elasticsearch Production Issues (and How Postgres Avoids Them)

Why Elasticsearch is complex in production: garbage collection, shard math, data sync pipelines, and monitoring overhead. Postgres with pg_textsearch simplifies search.

By Raja Rao DV

January 30th, 2026

Top 9 PostgreSQL Extensions Used by Tiger Data Customers in 2026

PostgreSQL Extensions

Tiger Data

You Don’t Need Elasticsearch: BM25 is Now in Postgres

You don't need Elasticsearch: BM25 is now in Postgres with pg_textsearch. Get better search rankings with term frequency, IDF, and length normalization.

By Raja Rao DV

December 23rd, 2025

Elasticsearch's Hybrid Search, Now in Postgres (BM25 + Vector + RRF)

It’s 2026, Just Use Postgres

10 Elasticsearch Production Issues (and How Postgres Avoids Them)

Top 9 PostgreSQL Extensions Used by Tiger Data Customers in 2026

You Don’t Need Elasticsearch: BM25 is Now in Postgres

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