Databricks
UnclaimedUnified analytics platform for data engineering and AI
TL;DR - Databricks
- Data lakehouse architecture
- Combines warehouse and lake benefits
- Unity Catalog governs all data
Pricing: Paid only
Best for: Enterprises & professionals
Score: 87/100
Pricing Plans
free trialCommunity Edition
Free
Learning
- Limited features
- Training
- Open source
Most Popular
Jobs Compute
$0.07-0.15/DBU
- Scheduled workloads
- 30-50% cheaper
- Automated jobs
All-Purpose
$0.20-0.40/DBU
- Interactive workloads
- Notebooks
- Exploration
SQL Compute
$0.22-0.65/DBU
- BI queries
- SQL analytics
- Dashboards
About Databricks
Databricks unifies data engineering, science, and analytics on a single platform. Process data at scale, train ML models, and run analytics—all on one lakehouse architecture without moving data between systems.
The notebook environment is collaborative. MLflow handles model lifecycle. Delta Lake provides reliable data storage.
Organizations with serious data and ML ambitions choose Databricks for a platform that handles everything from ingestion to production models.
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Databricks FAQ
Community Edition is free with limited resources. Otherwise, pay for compute (DBUs) on top of cloud costs. Can be expensive at scale.
Databricks is a unified data analytics platform. Built on Apache Spark for big data processing, ML, and analytics. Founded by Spark creators.
Databricks is better for ML and data engineering. Snowflake is better for data warehousing and analytics. Different strengths, often used together.
Unity Catalog is Databricks' data governance layer. Manage data access, lineage, and discovery across the lakehouse. Essential for enterprise.