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Milvus vs Zilliz

Zilliz scores higher on the AgentReady, 49/100 against 34/100. They differ on 9 of the 41 signals. Which ones decides whether an agent can adopt them without a person watching.

What each one is

Milvus. An open-source vector database built for GenAI applications.

Zilliz. Zilliz offers a fully managed Vector Lakebase powered by Milvus, unifying real-time vector search, lake-scale discovery, and AI data operations.

Where Milvus is ahead

Milvus passes no mandatory sales call and copyable quickstart, and Zilliz does not. That is adopt, whether an agent can get a key and make its first successful call without a human in the loop.

Where Zilliz is ahead

Zilliz passes clear canonical domain, clear product positioning and public docs discoverable, and Milvus does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds understand: authentication documented. Milvus misses it.

And on adopt, self-service signup and cli available. Milvus misses those.

Finally, on operate, observable execution. Milvus misses it.

What neither does

Both fail llms-full.txt / full agent docs, mcp discoverable, structured api reference, openapi / spec quality, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented, agent-compatible signup flow, programmatic credential creation, fast time to first request, mcp integration available, structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified. If your agent needs any of those, you will be building it yourself either way.

Score, pillar by pillar

The AgentReady splits into four pillars, scored separately, because a product can be easy to find and still impossible to adopt.

Discover is whether an agent can find the product at all without being told it exists. Zilliz leads 80 to 47. Milvus misses clear canonical domain, clear product positioning, public docs discoverable, llms-full.txt / full agent docs, mcp discoverable; Zilliz misses llms-full.txt / full agent docs, mcp discoverable.

Understand. Zilliz leads 31 to 23. Milvus misses structured api reference, openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented; Zilliz misses structured api reference, openapi / spec quality, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented.

Adopt. Zilliz leads 45 to 40. Milvus misses self-service signup, agent-compatible signup flow, programmatic credential creation, fast time to first request, cli available, mcp integration available; Zilliz misses no mandatory sales call, agent-compatible signup flow, programmatic credential creation, fast time to first request, copyable quickstart, mcp integration available.

Operate. Zilliz leads 39 to 24. Milvus misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, observable execution, agent compatibility verified; Zilliz misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified.

Pricing

Milvus does not publish a machine-readable starting price and has a free tier. Zilliz does not publish one and has a free tier.

Signal by signal

Which to pick

Zilliz clears more of the signals an agent needs, so it is the safer default for unattended use. Full profiles: Milvus and Zilliz. Alternatives to each: Milvus, Zilliz.

An agent can fetch this as data: POST /v1/compare {"slugs": ["milvus", "zilliz"]}