What it is
Databricks is a platform for working with large volumes of data: ingestion, transformation, SQL analytics, data science and AI models in one place. It uses a lakehouse architecture that keeps data in open formats like Delta Lake on your own cloud storage. It was founded by the creators of Apache Spark and runs on AWS, Azure and Google Cloud.
How to use it
- Transform data with Python, SQL or Scala notebooks and scheduled pipelines.
- Query and build dashboards with Databricks SQL, or ask in plain language with Genie.
- Govern access to tables, files and models with Unity Catalog.
- Train, track and serve AI models with MLflow and Mosaic AI.
- Learn for free with the Free Edition.
What it's good for
- A bank processing each day's transactions to detect fraud with its own models.
- A retailer combining sales, inventory and weather to forecast demand per store.
- A data science team moving models from notebooks to production with governance and lineage.
Pros
- Data in open formats (Delta Lake, Iceberg) on your own storage
- Data engineering, SQL and machine learning on one platform
- Runs on AWS, Azure and Google Cloud
- Free Edition for learning and experimenting
Cons
- Steep learning curve; you'll want data engineers on the team
- DBU billing on top of cloud infrastructure costs is hard to estimate
- Overkill for companies with little data or simple reporting
