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Databricks vs Vespa

Vespa scores higher on the AgentReady, 56/100 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

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.

Vespa. Vespa.ai develops the Vespa AI Search Platform, a distributed serving engine that unifies retrieval, ranking, machine learning inference, and real-time serving for business-critical AI applications.

Where Databricks is ahead

Databricks passes agent-compatible signup flow, and Vespa does not. That is adopt, whether an agent can get a key and make its first successful call without a human in the loop.

It also holds operate: agent compatibility verified. Vespa misses it.

Where Vespa is ahead

Vespa passes pricing understandable and limits / constraints documented, 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, free trial or free allowance, fast time to first request and copyable quickstart. Databricks misses those.

What neither does

Both fail mcp discoverable, openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented, no mandatory sales call, programmatic credential creation, mcp integration available, structured, predictable output, machine-readable errors, retry behavior documented, 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. Databricks misses mcp discoverable; Vespa misses mcp discoverable.

Understand. Vespa leads 46 to 31. Databricks misses openapi / spec quality, authentication documented, pricing understandable, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented; Vespa misses openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented.

Adopt is whether an agent can get a key and make its first successful call without a human in the loop. Vespa leads 55 to 35. 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; Vespa misses no mandatory sales call, agent-compatible signup flow, programmatic credential creation, mcp integration available.

Operate. Databricks leads 53 to 35. Databricks misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable; Vespa misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified.

Pricing

Databricks does not publish a machine-readable starting price. Vespa starts at $0.05/hour with no free tier.

Signal by signal

Which to pick

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

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