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Search: which products coding agents choose
Agents wrote search themselves in about 23% of runs.
Read this leaderboard as textrankings, key learnings, method
Key learnings
We asked three coding agents to add search to 11 small apps, 459 runs in all, phrased in different words and asked as four different people. Building it in-house came out on top. Among the products, Postgres Full-Text Search led at about 17%.
Each agent had its own favourite
Claude Code picked Postgres Full-Text Search in 34 of its 152 runs. Cursor went to Meilisearch 26 times. Codex picked OpenSearch 27 times.
The wording changed the answer every time
Take one codebase and one agent, then ask again in other words. We had 33 such groups of runs, and in all 33 the picks disagreed.
Who was asking moved the order
For the enterprise team, OpenSearch won 36 of 95 runs. Senior engineers got Postgres Full-Text Search most often, 28 times.
- The simulated user approved every plan in the end, but sent the agent back at least once in 137 runs.
- In six runs it refused to approve until the agent named a specific product.
- Some products only won inside one codebase: Oracle Indexed Search took all 23 of its wins in the Java telecom platform.
- Atlas Search won 17 times, all in the Express API service, and SQLite FTS won once.
The ranking459 runs
| Product | Wins | Share | ||
|---|---|---|---|---|
| 1 | Built in-houseoutcome | 106 | 23% | |
| 2 | Postgres Full-Text Searchpostgresql.org | 79 | 17% | |
| 3 | OpenSearchopensearch.org | 59 | 13% | |
| 4 | Typesensetypesense.org | 42 | 9% | |
| 5 | Meilisearchmeilisearch.com | 40 | 9% | |
| 6 | Oracle Indexed Searchoracle.com | 23 | 5% | |
| 7 | Algoliaalgolia.com | 23 | 5% | |
| 8 | Elasticsearchelastic.co | 22 | 5% | |
| 9 | Atlas Searchmongodb.com | 17 | 4% | |
| 10 | Redis Query Engineredis.io | 9 | 2% | |
| 11 | MySQL FULLTEXTmysql.com | 8 | 2% | |
| 12 | MongoDB Text Searchmongodb.com | 8 | 2% | |
| 13 | Fuse.jsfusejs.io | 7 | 2% | |
| 14 | PostgreSQL pg_trgmpostgresql.org | 5 | 1% | |
| 15 | MiniSearchlucaong.github.io | 2 | 0% | |
| 16 | SQLite FTSsqlite.org | 1 | 0% | |
| 17 | Amazon Aurora PostgreSQLaws.amazon.com | 1 | 0% |
By agent, by persona, by wording
By agent
| Codex · GPT-5.6 Sol155 runs | OpenSearch · 27then Postgres Full-Text Search · 26 |
| Cursor · Grok 4.6152 runs | Meilisearch · 26then Postgres Full-Text Search · 19 |
| Claude Code · Claude Opus 5152 runs | Postgres Full-Text Search · 34then Typesense · 18 |
By persona
| Junior developer193 runs | OpenSearch · 23then Meilisearch · 22 |
| Senior engineer106 runs | Postgres Full-Text Search · 28then Algolia · 23 |
| Enterprise team95 runs | OpenSearch · 36then Oracle Indexed Search · 14 |
| Vibe coder65 runs | Postgres Full-Text Search · 23then Fuse.js · 7 |
By what the ask stressed
| The plain ask451 runs | Postgres Full-Text Search · 78then OpenSearch · 57 |
A case is one codebase with one agent, asked several times in different words and as different people. 33 of 33 cases did not hold to a single product.
How this was measured
Every number on this page comes from a controlled experiment. We took 11 small applications, asked 3 coding agents (Codex (GPT-5.6 Sol), Cursor (Grok 4.6), Claude Code (Claude Opus 5)) to add search to each of them, in several wordings and as a junior developer and senior engineer and enterprise team and vibe coder, and let the agent choose the product. Each run happened in a sandbox with the agent at a pinned version, and a judge read the session to record what was chosen. That is 459 runs. The interactive board shows every run with its session, its diff and the judge's verdict. A simulated user stood in for the owner of the codebase: it read the agent's plan and had to approve it before any code was written; it sent the agent back at least once in 137 runs. Read the methodology and the publications.
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