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
-
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.
-
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.
-
Which is faster on dedicated search workloads?
Typesense
Dedicated C++ engine vs general-purpose database. For pure search, Typesense pulls ahead at scale.
-
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.
-
Which is cheaper?
Postgres Full-Text Search
No additional infrastructure. Typesense adds its own infra cost (or Cloud bill).
-
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.