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docs: Update DataFusion introduction to clarify that DataFusion does provide an "out of the box" query engine #12666

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docs: Update DataFusion introduction to clarify that DataFusion does provide an "out of the box" query engine #12666

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Update DataFusion introduction to show that DataFusion offers package…
andygrove Sep 28, 2024
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andygrove Sep 28, 2024
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17 changes: 14 additions & 3 deletions README.md
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</a>

DataFusion is an extensible query engine written in [Rust] that
uses [Apache Arrow] as its in-memory format. DataFusion's target users are
uses [Apache Arrow] as its in-memory format.

The core DataFusion libraries in this repository are not designed to be an out-of-the-box tool for end users. However,
the following subprojects offer packaged versions of DataFusion.

- [DataFusion Python](https://github.com/apache/datafusion-python/) offers a Python interface for SQL and DataFrame
queries.
- [DataFusion Ray](https://github.com/apache/datafusion-ray/) provides a distributed version of DataFusion that scales
out on Ray clusters.
- [DataFusion Comet](https://github.com/apache/datafusion-comet/) is an accelerator for Apache Spark based on
DataFusion.
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Note that I intentionally did not include Ballista here since it is not very active. If the project does become active again then we could add it to this list.


The target audience for the DataFusion crates in this repository are
developers building fast and feature rich database and analytic systems,
customized to particular workloads. See [use cases] for examples.

"Out of the box," DataFusion offers [SQL] and [`Dataframe`] APIs,
DataFusion offers [SQL] and [`Dataframe`] APIs,
excellent [performance], built-in support for CSV, Parquet, JSON, and Avro,
extensive customization, and a great community.
[Python Bindings] are also available.

DataFusion features a full query planner, a columnar, streaming, multi-threaded,
vectorized execution engine, and partitioned data sources. You can
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