Apache Spark SQL vs Databricks SQL
Apache Spark SQL: Spark's SQL and DataFrame engine for large-scale batch, streaming and lakehouse processing. Databricks SQL: Serverless SQL warehouses on the Databricks lakehouse, powered by the Photon C++ engine.
key differences
- Apache Spark SQL is primarily a relational database; Databricks SQL is columnar / OLAP.
- Licensing: Apache Spark SQL is open source (permissive) (Apache License 2.0); Databricks SQL is proprietary (Proprietary).
- Transactions: Apache Spark SQL offers limited ACID; Databricks SQL offers full.
- Only Apache Spark SQL has in-memory.
- Only Databricks SQL has transactions, vector search, geospatial, change data capture, materialized views.
- Databricks SQL has a serverless option; Apache Spark SQL does not.
choose apache-spark-sql for
- +Lakehouse ETL and ELT
- +Batch feature engineering for ML
- +Streaming ingestion into Delta/Iceberg
- +Large-scale data cleaning and joins
best at · Lakehouse, OLAP, Streaming
choose databricks-sql for
- +Lakehouse SQL and BI on Delta Lake
- +Consolidating a separate warehouse into Databricks
- +dbt transformations on the lakehouse
- +Serving features and aggregates for ML
best at · Lakehouse, Warehouse, OLAP
Apache Spark SQL vs Databricks SQL: FAQ
What is the difference between Apache Spark SQL and Databricks SQL?
Apache Spark SQL: Spark's SQL and DataFrame engine for large-scale batch, streaming and lakehouse processing. Databricks SQL: Serverless SQL warehouses on the Databricks lakehouse, powered by the Photon C++ engine. Apache Spark SQL is primarily a relational database; Databricks SQL is columnar / OLAP. Licensing: Apache Spark SQL is open source (permissive) (Apache License 2.0); Databricks SQL is proprietary (Proprietary). Transactions: Apache Spark SQL offers limited ACID; Databricks SQL offers full.
When should I choose Apache Spark SQL over Databricks SQL?
Choose Apache Spark SQL for lakehouse ETL and ELT; batch feature engineering for ML; and streaming ingestion into Delta/Iceberg. Choose Databricks SQL for lakehouse SQL and BI on Delta Lake; consolidating a separate warehouse into Databricks; and dbt transformations on the lakehouse.
Is Apache Spark SQL or Databricks SQL more popular?
Apache Spark SQL ranks #26 on the WhichDB Score (50.3/100) and Databricks SQL ranks #147 (20.8/100). Popularity is not fit: check the requirements that matter for your project.
Are Apache Spark SQL and Databricks SQL open source?
Yes. Apache Spark SQL is open source. License: Apache License 2.0. No. Databricks SQL is proprietary, closed-source software.