Databricks
What is Databricks?
Discover how Databricks can enhance your workflow
Key Capabilities
What makes Databricks powerful
Delta Pipelines
Handle streaming and batch with resilient Delta pipelines that lower ops toil and give you reliable tables for analytics and ML.
SQL Warehouses
Serve dashboards and ad hoc analysis with elastic compute catalogs lineage and predictable performance at scale.
MLflow and Features
Track experiments package models and ship online or batch inference with governance and reproducibility across teams.
Vector and RAG
Index enterprise content and enable assistants to answer with governed context and observability for safe usage.
Key Features
What makes Databricks stand out
- Lakehouse storage and compute that unifies batch streaming BI and ML on open formats for cost and portability across clouds
- Collaborative notebooks and repos that let data and ML teams build together with version control alerts and CI friendly patterns
- SQL Warehouses that power dashboards and ad hoc analysis with elastic clusters and fine grained governance via catalogs
- MLflow native integration for experiment tracking packaging registry and deployment that works across jobs and services
- Vector search and RAG building blocks that bring enterprise content into assistants under governance and observability
- Jobs and workflows that schedule pipelines with retries alerts and asset lineage visible in Unity Catalog for audits
Use Cases
How Databricks can help you
- Build governed data products that serve BI dashboards and ML models without copying data across silos
- Modernize ETL by shifting to Delta pipelines that handle streaming and batch with fewer moving parts and clearer lineage
- Deploy RAG assistants that search governed documents with vector indexes and access controls for safe retrieval
- Scale experimentation with MLflow so teams compare runs promote models and enable reproducible releases
- Consolidate legacy warehouses and data science clusters to reduce cost and drift while improving security posture
- Serve predictive features to apps using online stores that sync from batch and streaming pipelines under catalog control
- Power real time analytics by joining streams with historical data for operations and customer experiences
- Meet audit needs by tracing datasets models and dashboards through Unity Catalog with roles and row level policies
Perfect For
data engineers analytics leaders ML engineers platform teams and architects at companies that want a governed lakehouse for ETL BI and production AI with usage based pricing
Plans & Pricing
Free trial / Usage-based pay as you go
Visit official site for current pricing
Quick Information
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Frequently Asked Questions
How does pricing start?
Can I use my existing lake?
Do you support BI and ML together?
How do we manage governance?
Is there a free trial?
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