Databricks Agent Evaluation vs Amazon Bedrock Evaluations
Both are agent evaluation tools. Here is how they actually differ on price, billing model and deployment.
Databricks Agent Evaluation
Mosaic AI's agent evaluation, where tools are registered in Unity Catalog so the permissions protecting your data also scope what an agent may do. Judge Builder lets you tune the judges to your domain.
Amazon Bedrock Evaluations
AWS-native model and agent evaluation, billed per evaluation job. The recurring criticism is fragmentation - CloudWatch, Prompt Flows and Evaluations look like one product on paper and behave like three in practice.
| Databricks Agent Evaluation | Amazon Bedrock Evaluations | |
|---|---|---|
| Category | Agent Evaluation | Agent Evaluation |
| Our rating | 4/5 | 3/5 |
| Starting price | Databricks consumption | Per evaluation job |
| Billing meter | No usage metering | job |
| Free plan | No | No |
| Free self-hosting | No or paid tier only | No or paid tier only |
| Best for | Existing Databricks customers building agents over their own governed data, where inheriting Unity Catalog permissions and MLflow lineage is worth more than best-in-class conversation simulation. | Teams already committed to Bedrock who want evaluation inside their existing AWS account and IAM boundary, and who value procurement simplicity over best-in-class agent tooling. |
Our verdict on Databricks Agent Evaluation
Databricks Agent Evaluation has the best answer to a question most of this category ignores - what is an agent actually allowed to do. Tools are registered in Unity Catalog, so the same least-privilege permissions protecting your data also scope what an agent may access. That means agent authorisation is not a new system to design and audit, it is the one you already have, which is the most coherent approach to the problem we have encountered. The evaluation side is strong too. Built-in AI judges score correctness, relevance and safety, runs are tracked in MLflow so versions compare and regressions can gate deployment, and Agent-as-a-Judge, Tunable Judges and Judge Builder attack the genuine weakness of LLM-as-judge, which is that a generic judge does not understand your domain. The obvious constraint is that none of this exists outside Databricks. There is no standalone product, no separate pricing, and evaluation cost sits inside consumption where it is hard to isolate. If you are a Databricks shop building agents over your own data, this is close to automatic. If you are not, it is not a realistic option.
Full Databricks Agent Evaluation review →Our verdict on Amazon Bedrock Evaluations
Bedrock Evaluations is the sensible choice for a specific buyer - the team already on Bedrock - and unremarkable for anyone else. The argument is not capability, it is boundary. Everything stays inside your AWS account and IAM perimeter, there is no new vendor, no new contract and no new security review, and evaluation is billed per job rather than as a subscription so occasional use costs very little. For a regulated enterprise that has already cleared AWS, that combination resolves in one step what a specialist tool turns into a procurement project. The recurring criticism is fragmentation, and it is fair. CloudWatch metrics for Bedrock, Bedrock Prompt Flows and Bedrock Evaluations are described as three surfaces that feel like one on paper and three in practice, and that is the characteristic experience of AWS-native tooling - each piece works, and stitching them into a coherent workflow is your job. On agents specifically, AgentCore reached GA in October 2025 but Policy and Evaluations arrived in preview in December, so the agent evaluation story is newer than the headline suggests.
Full Amazon Bedrock Evaluations review →Frequently Asked Questions
What is the main difference between Databricks Agent Evaluation and Amazon Bedrock Evaluations?
Databricks Agent Evaluation: Existing Databricks customers building agents over their own governed data, where inheriting Unity Catalog permissions and MLflow lineage is worth more than best-in-class conversation simulation. Amazon Bedrock Evaluations: Teams already committed to Bedrock who want evaluation inside their existing AWS account and IAM boundary, and who value procurement simplicity over best-in-class agent tooling. Both sit in Agent Evaluation, so the decision usually comes down to billing model and deployment rather than raw capability.
Which is cheaper, Databricks Agent Evaluation or Amazon Bedrock Evaluations?
It depends entirely on your workload shape, because they meter differently - Databricks Agent Evaluation bills on no usage metering and Amazon Bedrock Evaluations bills on job. Published starting prices are Databricks consumption and Per evaluation job respectively, but those numbers are not comparable until you apply them to the same traffic. Use our cost calculator to model both against your own request volume and span count.
Can I self-host Databricks Agent Evaluation or Amazon Bedrock Evaluations?
Databricks Agent Evaluation: No or paid tier only. Amazon Bedrock Evaluations: No or paid tier only. Free self-hosting means no licence fee, not no cost - you still own the infrastructure, upgrades and on-call.