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Convex vs Databricks

Convex scores higher on the AgentReady, 61/100 against 52/100. 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

Convex. The reactive backend platform that keeps up with you and your agents.

Databricks. Databricks provides a Data + AI Platform to unify data, analytics and AI, enabling users to build and run apps, agents and AI on their data.

Where Convex is ahead

Convex passes pricing understandable, and Databricks does not. That is understand, whether an agent can read the docs and work out how the API behaves before calling it.

It also holds adopt: self-service signup, no mandatory sales call, free trial or free allowance, fast time to first request and copyable quickstart. Databricks misses those.

And on operate, retry behavior documented. Databricks misses it.

Where Databricks is ahead

Databricks passes structured api reference, and Convex does not. That is understand, whether an agent can read the docs and work out how the API behaves before calling it.

What neither does

Both fail mcp discoverable, openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented, programmatic credential creation, mcp integration available, structured, predictable output, machine-readable errors, idempotency support, rate-limit behavior predictable. 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 87/100 here. Convex misses mcp discoverable; Databricks misses mcp discoverable.

Understand. Databricks leads 31 to 23. Convex misses structured api reference, openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented; Databricks misses openapi / spec quality, authentication documented, pricing understandable, 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. Convex leads 76 to 35. Convex misses programmatic credential creation, mcp integration available; Databricks misses self-service signup, no mandatory sales call, programmatic credential creation, free trial or free allowance, fast time to first request, copyable quickstart, mcp integration available.

Operate. Convex leads 59 to 53. Convex misses structured, predictable output, machine-readable errors, idempotency support, rate-limit behavior predictable; Databricks misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable.

Pricing

Convex starts at $0/mo and has a free tier. Databricks does not publish one.

Signal by signal

Which to pick

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

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