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# Apache DataFusion
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[Website](https://datafusion.apache.org/) |
[API Docs](https://docs.rs/datafusion/latest/datafusion/) |
[Chat](https://discord.com/channels/885562378132000778/885562378132000781)
<a href="https://datafusion.apache.org/">
<img src="https://github.com/apache/datafusion/raw/HEAD/docs/source/_static/images/2x_bgwhite_original.png" width="512" alt="logo"/>
</a>
DataFusion is an extensible query engine written in [Rust] that
uses [Apache Arrow] as its in-memory format.
This crate provides libraries and binaries for developers building fast and
feature-rich database and analytic systems, customized for particular workloads.
See [use cases] for examples. The following related subprojects target end users:
- [DataFusion Python](https://github.com/apache/datafusion-python/) offers a Python interface for SQL and DataFrame
queries.
- [DataFusion Java](https://github.com/apache/datafusion-java/) offers a Java interface for SQL and DataFrame
queries.
- [DataFusion Comet](https://github.com/apache/datafusion-comet/) is an accelerator for Apache Spark based on
DataFusion.
- [DataFusion Ballista](https://github.com/apache/datafusion-ballista/) is a distributed query execution engine
that scales DataFusion across a cluster of nodes.
"Out of the box,"
DataFusion offers [SQL](https://datafusion.apache.org/user-guide/sql/index.html) and [DataFrame](https://datafusion.apache.org/user-guide/dataframe.html) APIs, excellent [performance],
built-in support for CSV, Parquet, JSON, and Avro, extensive customization, and
a great community.
DataFusion features a full query planner, a columnar, streaming, multi-threaded,
vectorized execution engine, and partitioned data sources. You can
customize DataFusion at almost all points including additional data sources,
query languages, functions, custom operators and more.
See the [Architecture] section for more details.
[rust]: http://rustlang.org
[apache arrow]: https://arrow.apache.org
[use cases]: https://datafusion.apache.org/user-guide/introduction.html#use-cases
[python bindings]: https://github.com/apache/datafusion-python
[performance]: https://benchmark.clickhouse.com/
[architecture]: https://datafusion.apache.org/contributor-guide/architecture.html
Here are links to important resources:
- [Project Site](https://datafusion.apache.org/)
- [Installation](https://datafusion.apache.org/user-guide/cli/installation.html)
- [Rust Getting Started](https://datafusion.apache.org/user-guide/example-usage.html)
- [Rust DataFrame API](https://datafusion.apache.org/user-guide/dataframe.html)
- [Rust API docs](https://docs.rs/datafusion/latest/datafusion)
- [Rust Examples](https://github.com/apache/datafusion/tree/main/datafusion-examples)
- [Python DataFrame API](https://datafusion.apache.org/python/)
- [Architecture](https://docs.rs/datafusion/latest/datafusion/index.html#architecture)
## What can you do with this crate?
DataFusion is great for building projects such as domain-specific query engines, new database platforms and data pipelines, query languages and more.
It lets you start quickly from a fully working engine, and then customize those features specific to your needs. See the [list of known users](https://datafusion.apache.org/user-guide/introduction.html#known-users).
## Contributing to DataFusion
Please see the [contributor guide] and [communication] pages for more information.
We discuss our [roadmap] via GitHub issues and invite you
to join the conversation. The current discussion is the
[DataFusion 2026 Q3-Q4 Roadmap Discussion].
[contributor guide]: https://datafusion.apache.org/contributor-guide
[communication]: https://datafusion.apache.org/contributor-guide/communication.html
[roadmap]: https://datafusion.apache.org/contributor-guide/roadmap.html
[datafusion 2026 q3-q4 roadmap discussion]: https://github.com/apache/datafusion/issues/22882
## Crate features
This crate has several [features] which can be specified in your `Cargo.toml`.
[features]: https://doc.rust-lang.org/cargo/reference/features.html
Default features:
- `nested_expressions`: functions for working with nested types such as `array_to_string`
- `compression`: reading files compressed with `xz2`, `bzip2`, `flate2`, and `zstd`
- `crypto_expressions`: cryptographic functions such as `md5` and `sha256`
- `datetime_expressions`: date and time functions such as `to_timestamp`
- `encoding_expressions`: `encode` and `decode` functions
- `parquet`: support for reading the [Apache Parquet] format
- `sql`: support for SQL parsing and planning
- `regex_expressions`: regular expression functions, such as `regexp_match`
- `unicode_expressions`: include Unicode-aware functions such as `character_length`
- `unparser`: enables support to reverse LogicalPlans back into SQL
- `recursive_protection`: uses [recursive](https://docs.rs/recursive/latest/recursive/) for stack overflow protection.
Optional features:
- `avro`: support for reading the [Apache Avro] format
- `backtrace`: include backtrace information in error messages
- `parquet_encryption`: support for using [Parquet Modular Encryption]
- `serde`: enable arrow-schema's `serde` feature
[apache avro]: https://avro.apache.org/
[apache parquet]: https://parquet.apache.org/
[parquet modular encryption]: https://parquet.apache.org/docs/file-format/data-pages/encryption/
## DataFusion API Evolution and Deprecation Guidelines
Public methods in Apache DataFusion evolve over time: while we try to maintain a
stable API, we also improve the API over time. As a result, we typically
deprecate methods before removing them, according to the [deprecation guidelines].
[deprecation guidelines]: https://datafusion.apache.org/contributor-guide/api-health.html
## Dependencies and `Cargo.lock`
Following the [guidance] on committing `Cargo.lock` files, this project commits
its `Cargo.lock` file.
CI uses the committed `Cargo.lock` file, and dependencies are updated regularly
using [Dependabot] PRs.
[guidance]: https://blog.rust-lang.org/2023/08/29/committing-lockfiles.html
[dependabot]: https://docs.github.com/en/code-security/dependabot/working-with-dependabot