Head-to-head · ML Experiment Tracking Software
Amazon SageMaker Experiments vs Databricks Mosaic AI
Amazon SageMaker Experiments leads on 0 checks, Databricks Mosaic AI on 0, and 5 are even. Who comes out ahead on the 5 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.
Our verdict
- Highest scoreAmazon SageMaker Experiments · 8.6/10
- Free trialonly Databricks Mosaic AI
- Most featuresAmazon SageMaker Experiments · 4 of 5
Amazon SageMaker Experiments scores higher on our rubric for ml experiment tracking software: 8.6 against 8.5 out of 10; our editors rank them #4 and #5.
Amazon SageMaker Experiments is the better fit for AWS-native ML teams. Databricks Mosaic AI is the better fit for databricks lakehouse teams.
- Amazon SageMaker Experiments fits best
AWS-native ML teams
- Databricks Mosaic AI fits best
Databricks lakehouse teams
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Side by side
| Feature | Amazon SageMaker Experiments 8.6/10 Visit ↗ | Databricks Mosaic AI 8.5/10 Visit ↗ |
|---|---|---|
| At a glance | ||
| Editor score | 8.6 | 8.5 |
| Ranking | #4 in ML Experiment Tracking Software | #5 in ML Experiment Tracking Software |
| Best for | AWS-native ML teams | Databricks lakehouse teams |
| Pricing model | Paid | Paid |
| Starting price | — | — |
| Free plan | — | Not checked yet |
| Free trial | — | 14 days |
| Deployment | Cloud | Cloud |
| Platforms | Web | Web |
| Support | Docs | Docs |
| Built for | Small business, Mid-market, Enterprise | Mid-market, Enterprise |
| Features Amazon SageMaker Experiments 4/5 · Databricks Mosaic AI 1/5 | ||
| Run comparison | ✓ (best) | Not checked yet |
| Artifact tracking | ✓ (best) | Not checked yet |
| Dataset versioning | Not checked yet | Not checked yet |
| Model registry | ✓ | ✓ |
| API and SDK access | ✓ (best) | Not checked yet |
| Specs | ||
| Deployment options | Cloud | Not checked yet |
| Our review | ||
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| Our verdict | Amazon SageMaker Experiments helps data scientists and developers organize, track, analyze, and compare machine learning experiments and training runs. It supports inputs, parameters, configurations, metrics, results, and output artifacts,… Read the review → |
Databricks Mosaic AI is a cloud-based platform for developing, deploying, monitoring, and governing machine-learning and generative-AI applications. It is aimed at organizations and technical teams building production AI systems across… Read the review → |
Strengths and trade-offs
Amazon SageMaker Experiments — where it wins
- Tracks parameters, metrics, configurations, results, and artifacts
- Compares experiment runs with metrics and charts
- Connects MLflow, S3, registries, pipelines, APIs, and SDKs
Where it doesn't
- No free plan
- Compute and storage are billed separately
- Best suited to teams already centered on AWS services
Databricks Mosaic AI — where it wins
- MLflow tracking covers parameters, metrics, artifacts, runs, and code versions
- Combines registry, serving, workflows, compute, data history, and monitoring
- Unity Catalog integration supports centralized model governance
Where it doesn't
- Paid usage-based billing can make costs vary by provider, region, and services
- Committed Use Contracts require committed usage to access available discounts
- Its broad scope may exceed the needs of teams seeking experiment tracking alone
- Amazon SageMaker Experiments8.6/10 · Paid
A strong fit for AWS-native teams that need tracking, comparison, artifacts, and MLflow.
Visit AWSFull verdict → - Databricks Mosaic AI8.5/10 · 14-day trial
A broad ML platform for Databricks teams that need tracking through production operations.
Visit DatabricksFull verdict →
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Last updated · How we research and update