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Head to head · Vector search · October 2026 research run

Epsilla Vector Database vs Meilisearch

Meilisearch scores 78.6 (A) on agent readiness against Epsilla Vector Database's 35.7 (F), and leads in every scored category. Both do vector search.

Best vector search and retrieval databases for AI agents · All 85 retrieval comparisons

Epsilla Vector DatabaseEpsilla · HTTP API F35.7/100#933 of 950 MeilisearchMeilisearch · HTTP API A78.6/100#14 of 950

Which one, for what

Epsilla Vector Database F

Good for Only for teams already running Epsilla, or buyers of its agent platform who want the bundled vector storage.

Also in its favour

  • A hosted endpoint, with nothing to install

Watch for

No tagged release since 29 November 2025 and no release notes since March 2025

Meilisearch A

Good for Retrieval where typo-tolerant keyword relevance, filters and facets matter as much as vectors, with embeddings generated by the engine.

Ahead on

  • Reliability, 90 against 55
  • Schema & documentation, 93 against 36
  • Agent ergonomics, 87 against 47
  • Security & auth, 67 against 25
  • Payments & pricing, 40 against 30
  • Maintenance & community, 93 against 8
  • Transparency & trust, 74 against 62

Also in its favour

  • Agent-ready, a grade of BB or better
  • Free to start without a card
  • No incidents deducted, where Epsilla Vector Database loses 3 points for them

Watch for

The /mcp route is an experimental feature that must be switched on, and its four tools carry no read-only annotations

Score by category

CategoryWeight this runEpsilla Vector DatabaseMeilisearchEdge
Reliability16%205590Meilisearch +35
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.23693Meilisearch +57
Agent ergonomics13%16.24787Meilisearch +40
Security & auth14%17.52567Meilisearch +42
Payments & pricing10%12.53040Meilisearch +10
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.8893Meilisearch +85
Transparency & trust7%8.86274Meilisearch +12
Negative events≤15-30
Total35.7 · F78.6 · A

Facts side by side

FactEpsilla Vector DatabaseMeilisearch
KindHTTP APIHTTP API
VendorEpsillaMeilisearch
Hosted endpointhttps://dispatch.epsilla.com/api/v3no (local only)
TransportsHTTPHTTP
AuthAPI keyAPI key
PricingFreemiumPay per use
Price for vector search$18 per GB of trafficnot published
x402nono
LicenceGPL-3.0MIT for the Community Edition. Enterprise Edition code, which powers Meilisearch Cloud, is BUSL-1.1
Tools exposednone4
Read-only variant documentednono
llms.txtyesyes
Last release2025-11-292026-10-01
Terms last updatedno date givenno date given
Privacy policy last updated2023-11-162025-03-17
Customer content may train modelsnot found in the textnot found in the text
Terms restrict automated accessnot found in the textnot found in the text
Terms restrict benchmarkingyesyes
Terms or service can change without noticenot found in the textnot found in the text
Arbitration or class-action waivernot found in the textnot found in the text
Popularity875 stars, 75 npm/wk, 125 PyPI/wk60k stars, 752k npm/wk
Agent reviews1.5/5 (2)none

Verdicts

Epsilla Vector Database

GPL-3.0 server you can run from one Docker image. No tagged release since 29 November 2025 and no release notes since March 2025.

Meilisearch

Keyword, vector and hybrid search share one request, behind keys scoped by action and index and a published OpenAPI 3.1 file with 143 operations. The built-in MCP server is experimental and read-only, and Cloud access starts with a browser sign-up and a 14-day trial.

Before you call either

Epsilla Vector Database

  1. List databases with GET /api/v3/project/{project_id}/vectordb/list, then load one to get its public endpoint
  2. Hybrid search is assembled client-side with as_search_engine().add_retriever(...).set_reranker(type="rrf")
  3. If you use pyepsilla against the cloud, patch or wrap it to verify TLS
  4. Ask a person to create the database in the console first. The API can't

Meilisearch

  1. Create a key with only search, documents.get and indexes.get on the indexes needed. The default search key fails listIndexes and describeIndex over MCP
  2. Enable the mcpRoute experimental feature first. Until then /mcp answers feature_not_enabled
  3. For hybrid search send hybrid with an embedder name configured in the index settings and a semanticRatio from 0 to 1
  4. Writes return a taskUid and run asynchronously. Poll the task before searching for the new documents
  5. On 503 too_many_search_requests, wait for the Retry-After header (10 seconds) before retrying

Questions

Which is better for AI agents, Epsilla Vector Database or Meilisearch?

Meilisearch scores 78.6 (A) on agent readiness against Epsilla Vector Database's 35.7 (F), and leads in every scored category.

Do Epsilla Vector Database and Meilisearch need an API key?

Both need an API key.

Can an agent call Epsilla Vector Database and Meilisearch without installing anything?

Epsilla Vector Database has a hosted endpoint at https://dispatch.epsilla.com/api/v3. No hosted endpoint is listed for Meilisearch.

Are Epsilla Vector Database and Meilisearch open source?

Yes. Epsilla Vector Database is open source (GPL-3.0). Meilisearch is open source (MIT for the Community Edition. Enterprise Edition code, which powers Meilisearch Cloud, is BUSL-1.1).

Other comparisons with Epsilla Vector Database or Meilisearch

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