Inverted indexes are the perfect structure for text search.
This is a dev post classified by Jev as Databases (a launch), kept by the Dev Radar because it carries real work, not commentary.
Inverted indexes are the perfect structure for text search. "Inverted" here doesn't mean upside-down. Rather that it's an inversion of the original data. We take every distinct word from a set of documents and build a "posting list" of references back to every location where that word is used. When structured right, this lets databases like Postgres do fast lookup of words and phrases. TIN takes all this to the next level for Postgres. Span queries, fuzzy matching, wildcard matching, regex. All while strictly holding to Postgres durability, replication, and transactional semantics. Also, i
Posted by Ben Dicken (47.4k followers) 3 days ago · 537 likes · 31.7k views · view the original post on X. Kept by the Dev Radar as Databases.
More dev work like this
- Construct a bitemporal knowledge graph with Utopia that evolves as material arrives and… — @tom_doerr
- We’re bringing Databricks Unity Gateway to developers on Neon (@neondatabase), and it’s… — @Yuchenj_UW
- Docs changes shouldn’t need a mystery deployment process. — @DanKornas
- Our new short course with @DeepLearningAI covers continual and adaptive learning: the… — @OracleDevs
- The workshop you were looking for: 2 hours, virtual, and for free. — @neo4j
- Warehouse data shouldn’t wait for someone to ask the right question. — @DanKornas
- Context. That's the difference between an AI demo and a reliable production agent. The… — @Redisinc
- When #DuckDB-Wasm was launched in 2021, databases could not be persisted: everything… — @duckdb
Every post is read and classified by Jev (TypeSafe): what it is, which market it belongs to, and whether the link is a real tool. 12.2k posts from 4.7k X accounts over the last 21 days, 1.4k tools, 12 markets. Collected every 5 minutes, fully re-ranked every hour — last update 2026-09-19 18:39 UTC. Full method.