Frequently Asked Questions¶
What is the relationship between Apache Arrow, DataFusion, and Ballista?¶
Apache Arrow is a library which provides a standardized memory representation for columnar data. It also provides “kernels” for performing common operations on this data.
DataFusion is a library for executing queries in-process using the Apache Arrow memory model and computational kernels. It is designed to run within a single process, using threads for parallel query execution.
Ballista is a distributed compute platform built on DataFusion.
How does DataFusion Compare with
When compared to similar systems, DataFusion typically is:
Targeted at developers, rather than end users / data scientists.
Designed to be embedded, rather than a complete file based SQL system.
Governed by the Apache Software Foundation process, rather than a single company or individual.
Rust, rather than
Here is a comparison with similar projects that may help understand when DataFusion might be suitable or unsuitable for your needs:
DuckDB is an open source, in process analytic database. Like DataFusion, it supports very fast execution, both from its custom file format and directly from parquet files. Unlike DataFusion, it is written in C/C++ and it is primarily used directly by users as a serverless database and query system rather than as a library for building such database systems.
Polars: Polars is one of the fastest DataFrame libraries at the time of writing. Like DataFusion, it is also written in Rust and uses the Apache Arrow memory model, but unlike DataFusion it is not designed with as many extension points.
Facebook Velox is an execution engine. Like DataFusion, Velox aims to provide a reusable foundation for building database-like systems. Unlike DataFusion, it is written in C/C++ and does not include a SQL frontend or planning / optimization framework.
Databend is a complete database system. Like DataFusion it is also written in Rust and utilizes the Apache Arrow memory model, but unlike DataFusion it targets end-users rather than developers of other database systems.