DataFusion is an extensible query execution framework, written in Rust, that uses Apache Arrow as its in-memory format.

DataFusion supports both an SQL and a DataFrame API for building logical query plans as well as a query optimizer and execution engine capable of parallel execution against partitioned data sources (CSV and Parquet) using threads.

DataFusion also supports distributed query execution via the Ballista crate.

DataFusion is used to create modern, fast and efficient data pipelines, ETL processes, and database systems, which need the performance of Rust and Apache Arrow and want to provide their users the convenience of an SQL interface or a DataFrame API.

• High Performance: Leveraging Rust and Arrow's memory model, DataFusion achieves very high performance
• Easy to Connect: Being part of the Apache Arrow ecosystem (Arrow, Parquet and Flight), DataFusion works well with the rest of the big data ecosystem
• Easy to Embed: Allowing extension at almost any point in its design, DataFusion can be tailored for your specific usecase
• High Quality: Extensively tested, both by itself and with the rest of the Arrow ecosystem, DataFusion can be used as the foundation for production systems.

Projects that adapt to or serve as plugins to DataFusion:

• datafusion-python
• datafusion-java
• datafusion-objectstore-s3
• datafusion-objectstore-hdfs
• datafusion-bigtable
• datafusion-objectstore-azure

Here are some of the projects known to use DataFusion:

• Ballista Distributed Compute Platform
• Cloudfuse Buzz
• Cube Store
• delta-rs
• Flock
• InfluxDB IOx Time Series Database
• ROAPI
• Tensorbase
• VegaFusion Server-side acceleration for the Vega visualization grammar

(if you know of another project, please submit a PR to add a link!)

Please see example usage to find how to use DataFusion.

Please see Roadmap for information of where the project is headed.

There is no formal document describing DataFusion's architecture yet, but the following presentations offer a good overview of its different components and how they interact together.

• (March 2021): The DataFusion architecture is described in Query Engine Design and the Rust-Based DataFusion in Apache Arrow: recording (DataFusion content starts ~ 15 minutes in) and slides
• (February 2021): How DataFusion is used within the Ballista Project is described in *Ballista: Distributed Compute with Rust and Apache Arrow: recording

Please see User Guide for more information about DataFusion.

Please see Contribution Guide for information about contributing to DataFusion.