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Qdrant vs Zilliz

Qdrant scores higher on the AgentReady, 58/100 against 49/100. They differ on 8 of the 41 signals. Which ones decides whether an agent can adopt them without a person watching.

What each one is

Qdrant. Qdrant is a high-performance vector search engine that helps build AI retrieval systems.

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

Where Qdrant is ahead

Qdrant passes mcp discoverable, and Zilliz does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds understand: structured api reference. Zilliz misses it.

And on adopt, no mandatory sales call, fast time to first request, copyable quickstart and mcp integration available. Zilliz misses those.

Where Zilliz is ahead

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

It also holds operate: observable execution. Qdrant misses it.

What neither does

Both fail llms-full.txt / full agent docs, openapi / spec quality, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented, agent-compatible signup flow, programmatic credential creation, 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. Both sit at 80/100 here. Qdrant misses public docs discoverable, llms-full.txt / full agent docs; Zilliz misses llms-full.txt / full agent docs, mcp discoverable.

Understand. Qdrant leads 46 to 31. Qdrant misses openapi / spec quality, 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 is whether an agent can get a key and make its first successful call without a human in the loop. Qdrant leads 80 to 45. Qdrant misses agent-compatible signup flow, programmatic credential creation; 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. Qdrant 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

Qdrant 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

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

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