AWS SageMaker vs Databricks: Which is Better in 2026?
Choosing between AWS SageMaker and Databricks comes down to understanding what each tool does best. This comparison breaks down the key differences so you can make an informed decision based on your specific needs, not marketing claims.
Bottom line: Databricks wins this matchup. MongoDB is our overall Cloud & Infrastructure pick. MongoDB is our free Cloud & Infrastructure pick. Pick AWS SageMaker if you need AI & automation.
Short on time? Here's the quick answer
Based on published vendor pricing and features and on public review data, here's who should pick what:
AWS SageMaker
The integrated studio for building, training, and deploying AI and ML models with unified data access.
Best for you if:
- • You want comprehensive suite of tools covering the entire AI lifecycle
Databricks
Unified analytics for data engineering, science, and ML
Best for you if:
- • You want unified platform
| At a Glance | AWS SageMaker | Databricks |
|---|---|---|
Starts at | Custom | Custom |
Category | AI & Automation Cloud & Infrastructure | Data & Databases Analytics |
Rating | 3.0/5 Trustpilot 1.3 · G2 4.3 · Capterra 4.7 131 reviews | 4.6/5 G2 4.6 · Capterra 4.5 1,385 reviews |
Free plan | No | No |
Watch out for | n/a | Separate cloud infrastructure bill on top of DBUs, varying with instance types and usage |
Choose AWS SageMaker or Databricks?
Choose AWS SageMaker if
- You want comprehensive suite of tools covering the entire AI lifecycle
- You want unified access to diverse data sources through a lakehouse architecture
- You work in AI & automation, not data & databases
Choose Databricks if
- You want unified platform
- You want great collaboration
- You work in data & databases, not AI & automation
In-Depth Analysis
AWS SageMaker
The integrated studio for building, training, and deploying AI and ML models with unified data access.
Strengths
- Pro: Comprehensive suite of tools covering the entire AI lifecycle
- Pro: Unified access to diverse data sources through a lakehouse architecture
- Pro: Strong emphasis on enterprise-grade security and governance
- Pro: Accelerates development with AI assistance and managed infrastructure
- Pro: Seamless integration with other AWS services like Amazon Redshift and S3
Weaknesses
- Con: Can have a steep learning curve for new users unfamiliar with AWS ecosystem
- Con: Cost can become significant for large-scale or complex workloads
- Con: Requires careful management of AWS resources to optimize performance and cost
Key features
Databricks
Unified analytics for data engineering, science, and ML
It's best for enterprises with significant data processing needs and budgets to match.
Watch out
Separate cloud infrastructure bill on top of DBUs, varying with instance types and usage
Strengths
- Pro: Unified platform
- Pro: Great collaboration
- Pro: Delta Lake
Weaknesses
- Con: Expensive at scale
- Con: Complex dual billing (DBU plus cloud infra)
- Con: Steep learning curve
Key features
Pricing: AWS SageMaker vs Databricks
| Plan | AWS SageMaker | Databricks |
|---|---|---|
| Tier 1 | N/A | Community Edition |
| Tier 2 | N/A | /DBU Jobs Compute |
| Tier 3 | N/A | /DBU All-Purpose |
| Tier 4 | N/A | /DBU SQL Compute |
Pricing verified from each vendor's public pricing page. Compare in detail on AWS SageMaker pricing and Databricks pricing.
Key Takeaways
Databricks
- Higher user rating: 4.6/5 vs 3.0/5
- Larger review base (1,385 reviews)
- Our pick for this comparison
AWS SageMaker
- Better fit for AI & automation
The Bottom Line
Databricks wins this matchup. MongoDB is our overall Cloud & Infrastructure pick. MongoDB is our free Cloud & Infrastructure pick.
Frequently Asked Questions
Is AWS SageMaker or Databricks better in 2026?
Databricks wins this matchup. MongoDB is our overall Cloud & Infrastructure pick. MongoDB is our free Cloud & Infrastructure pick. Pick AWS SageMaker for AI & automation workflows (main strength: comprehensive suite of tools covering the entire AI lifecycle). Pick Databricks for data & databases workflows (main strength: unified platform).
What are AWS SageMaker and Databricks used for?
AWS SageMaker: The integrated studio for building, training, and deploying AI and ML models with unified data access. Databricks: Unified analytics for data engineering, science, and ML.
What does AWS SageMaker cost vs Databricks?
AWS SageMaker pricing is on their site. Databricks pricing is on their site.
What's the main difference between AWS SageMaker and Databricks?
AWS SageMaker's main strength: comprehensive suite of tools covering the entire AI lifecycle. Databricks's main strength: unified platform.