Databricks
Definition
Unified analytics platform on Apache Spark combining data lake storage with warehouse reliability (Lakehouse), plus collaborative notebooks for data teams.
Use Cases
- Shell: Predictive maintenance for oil rigs — Shell uses Databricks to process large volumes of sensor data from oil rigs to predict equipment failures using machine learning models. (Improved equipment uptime and reduced maintenance costs by predicting failures before they occur.)
Provider Equivalents
- AWS: Amazon EMR
- Azure: Azure Databricks
- GCP: Google Cloud Dataproc
Frequently Asked Questions
- What's the difference between Databricks and Apache Spark?
- Databricks is a managed platform built on Apache Spark, offering additional features like collaborative notebooks, optimized data storage with Delta Lake, and easier integration with other data tools.
- When should I use Databricks?
- Use Databricks when you need to process large datasets with Apache Spark, require collaborative data science environments, or want to unify data engineering and machine learning workflows.
- How much does Databricks cost?
- Databricks pricing is based on compute usage, typically measured in Databricks Units (DBUs), which vary depending on the instance type and workload. Additional costs may include storage and data transfer.
Category: data
Difficulty: advanced
Related Terms
See Also