Postgres Full-Text Search vs Typesense, which search engine wins for your brief, in 2026
Two search engines, side by side. Postgres Full-Text Search is built into postgres. free, no separate service, good enough for most apps. Typesense is open-source search server, algolia-shape api. self-host or typesense cloud. The verdict, the criteria, and the honest take below.
ALL SEARCH COMPARISONS →Verdict in one paragraph
In-database FTS vs dedicated search engine. Postgres FTS wins on simplicity (no second service) and the ability to query search + relational data in one round trip. Typesense wins on typo tolerance, instant-search UX, and dedicated-engine performance. For most apps with Postgres in the stack, Postgres FTS is sufficient; Typesense is for when search becomes a real product feature.
Score: Postgres Full-Text Search 3 · Typesense 3
Side by side
Decision criteria
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Which has lower operational overhead?
Postgres Full-Text Search
Postgres FTS is part of Postgres, no separate service. Typesense is a separate engine to run.
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Which has better typo tolerance?
Typesense
Typesense ships Algolia-grade typo tolerance out of the box. Postgres FTS via pg_trgm gets close but the ergonomics differ.
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Which is faster on dedicated search workloads?
Typesense
Dedicated C++ engine vs general-purpose database. For pure search, Typesense pulls ahead at scale.
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Which lets you query search + relational data in one query?
Postgres Full-Text Search
Single SQL query joins ts_rank + foreign keys + JSON columns. Typesense requires a separate store + app-level join.
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Which is cheaper?
Postgres Full-Text Search
No additional infrastructure. Typesense adds its own infra cost (or Cloud bill).
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Which is the right pick when search is a real product feature?
Typesense
When search is the product (e-commerce, content discovery, knowledge base), Typesense is the cleaner default.
What Postgres Full-Text Search is best for
- Apps already on Postgres where adding a search service is overhead
- Mid-scale workloads (under ~10M rows) where Postgres performance suffices
- Hybrid lexical + vector search via pg_trgm + pgvector + tsvector together
- Cost-conscious teams that want zero additional infrastructure
Read the full Postgres Full-Text Search entry: /search/postgres-fts/
What Typesense is best for
- Algolia-shape workloads at a fraction of the cost
- Self-hosted search with InstantSearch-compatible UI
- Mid-market e-commerce with budget constraints
- Apps that need vector + lexical hybrid without the Elastic operational footprint
Read the full Typesense entry: /search/typesense/
The search engine choice is the easy half, your relevance design is the hard one
The hard half is your typo tolerance, synonym dictionary, relevance tuning, and the analytics loop. The 30-min call is where you describe your corpus and your conversion bar; I tell you whether Postgres Full-Text Search or Typesense (or something else) is your fit.