Apache Spark SQL vs Presto
Apache Spark SQL: Spark's SQL and DataFrame engine for large-scale batch, streaming and lakehouse processing. Presto: Distributed SQL query engine from Meta for interactive queries over data lakes and many sources.
key differences
- Only Apache Spark SQL has in-memory, durable persistence, compression, streaming ingest.
- Only Presto has geospatial, role-based access, time travel.
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 presto for
- +Interactive SQL on data lakes
- +Federated queries across sources
- +Lakehouse analytics on Iceberg/Hudi
best at · OLAP, Lakehouse, Warehouse
Apache Spark SQL vs Presto: FAQ
What is the difference between Apache Spark SQL and Presto?
Apache Spark SQL: Spark's SQL and DataFrame engine for large-scale batch, streaming and lakehouse processing. Presto: Distributed SQL query engine from Meta for interactive queries over data lakes and many sources. Only Apache Spark SQL has in-memory, durable persistence, compression, streaming ingest. Only Presto has geospatial, role-based access, time travel.
When should I choose Apache Spark SQL over Presto?
Choose Apache Spark SQL for lakehouse ETL and ELT; batch feature engineering for ML; and streaming ingestion into Delta/Iceberg. Choose Presto for interactive SQL on data lakes, federated queries across sources and lakehouse analytics on Iceberg/Hudi.
Is Apache Spark SQL or Presto more popular?
Apache Spark SQL ranks #26 on the WhichDB Score (50.3/100) and Presto ranks #53 (37.7/100). Popularity is not fit: check the requirements that matter for your project.
Are Apache Spark SQL and Presto open source?
Yes. Apache Spark SQL is open source. License: Apache License 2.0. Yes. Presto is open source. License: Apache License 2.0.