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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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2b1e183
Update DataFusion introduction to show that DataFusion offers package…
andygrove Sep 28, 2024
f8a668f
change order
andygrove Sep 28, 2024
8731834
Update README.md
andygrove Oct 1, 2024
b061012
refine wording and update user guide for consistency
andygrove Oct 1, 2024
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prettier
alamb Oct 3, 2024
488c3fc
Merge remote-tracking branch 'apache/main' into datafusion-for-end-users
alamb Oct 3, 2024
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17 changes: 14 additions & 3 deletions README.md
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Expand Up @@ -42,14 +42,25 @@
</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 DataFusion libraries in this repository are used to build data-centric system software. DataFusion also provides the
following subprojects, which are packaged versions of DataFusion intended for end users.

- [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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15 changes: 14 additions & 1 deletion docs/source/index.rst
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Expand Up @@ -34,7 +34,20 @@ Apache DataFusion


DataFusion is an extensible query engine written in `Rust <http://rustlang.org>`_ that
uses `Apache Arrow <https://arrow.apache.org>`_ as its in-memory format. DataFusion's target users are
uses `Apache Arrow <https://arrow.apache.org>`_ as its in-memory format.

This documentation is for the <a href="https://github.com/apache/datafusion">core DataFusion project</a>, which contains
libraries that are used to build data-centric system software. DataFusion also offers the following subprojects, which
provide packaged versions of DataFusion intended for end users, and these have separate documentation.

- <a href="https://datafusion.apache.org/python/">DataFusion Python</a> offers a Python interface for SQL and DataFrame
queries.
- <a href="https://github.com/apache/datafusion-ray/">DataFusion Ray</a> provides a distributed version of DataFusion
that scales out on <a href="https://www.ray.io">Ray</a> clusters.
- <a href="https://datafusion.apache.org/comet/">DataFusion Comet</a> is an accelerator for Apache Spark based on
DataFusion.

DataFusion's target users are
developers building fast and feature rich database and analytic systems,
customized to particular workloads. See `use cases <https://datafusion.apache.org/user-guide/introduction.html#use-cases>`_ for examples.

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