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42 | 42 | </a>
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43 | 43 |
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44 | 44 | DataFusion is an extensible query engine written in [Rust] that
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45 |
| -uses [Apache Arrow] as its in-memory format. DataFusion's target users are |
| 45 | +uses [Apache Arrow] as its in-memory format. |
| 46 | + |
| 47 | +The DataFusion libraries in this repository are used to build data-centric system software. DataFusion also provides the |
| 48 | +following subprojects, which are packaged versions of DataFusion intended for end users. |
| 49 | + |
| 50 | +- [DataFusion Python](https://github.com/apache/datafusion-python/) offers a Python interface for SQL and DataFrame |
| 51 | + queries. |
| 52 | +- [DataFusion Ray](https://github.com/apache/datafusion-ray/) provides a distributed version of DataFusion that scales |
| 53 | + out on Ray clusters. |
| 54 | +- [DataFusion Comet](https://github.com/apache/datafusion-comet/) is an accelerator for Apache Spark based on |
| 55 | + DataFusion. |
| 56 | + |
| 57 | +The target audience for the DataFusion crates in this repository are |
46 | 58 | developers building fast and feature rich database and analytic systems,
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47 | 59 | customized to particular workloads. See [use cases] for examples.
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48 | 60 |
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49 |
| -"Out of the box," DataFusion offers [SQL] and [`Dataframe`] APIs, |
| 61 | +DataFusion offers [SQL] and [`Dataframe`] APIs, |
50 | 62 | excellent [performance], built-in support for CSV, Parquet, JSON, and Avro,
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51 | 63 | extensive customization, and a great community.
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52 |
| -[Python Bindings] are also available. |
53 | 64 |
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54 | 65 | DataFusion features a full query planner, a columnar, streaming, multi-threaded,
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55 | 66 | vectorized execution engine, and partitioned data sources. You can
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