docs/source/user-guide/introduction.md - datafusion - Git at Google

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 # Introduction

 DataFusion is an extensible query execution framework, written in
 Rust, that uses [Apache Arrow](https://arrow.apache.org) as its
 in-memory format.

 DataFusion supports SQL and a DataFrame API for building logical query
 plans, an extensive query optimizer, and a multi-threaded parallel
 execution execution engine for processing partitioned data sources
 such as CSV and Parquet files extremely quickly.

 ## Use Cases

 DataFusion is used to create modern, fast and efficient data
 pipelines, ETL processes, and database systems, which need the
 performance of Rust and Apache Arrow and want to provide their users
 the convenience of an SQL interface or a DataFrame API.

 ## Why DataFusion?

 - _High Performance_: Leveraging Rust and Arrow's memory model, DataFusion is very fast.
 - _Easy to Connect_: Being part of the Apache Arrow ecosystem (Arrow, Parquet and Flight), DataFusion works well with the rest of the big data ecosystem
 - _Easy to Embed_: Allowing extension at almost any point in its design, DataFusion can be tailored for your specific usecase
 - _High Quality_: Extensively tested, both by itself and with the rest of the Arrow ecosystem, DataFusion can be used as the foundation for production systems.
	<!---
	Licensed to the Apache Software Foundation (ASF) under one
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	"License"); you may not use this file except in compliance
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	Unless required by applicable law or agreed to in writing,
	software distributed under the License is distributed on an
	"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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	# Introduction

	DataFusion is an extensible query execution framework, written in
	Rust, that uses [Apache Arrow](https://arrow.apache.org) as its
	in-memory format.

	DataFusion supports SQL and a DataFrame API for building logical query
	plans, an extensive query optimizer, and a multi-threaded parallel
	execution execution engine for processing partitioned data sources
	such as CSV and Parquet files extremely quickly.

	## Use Cases

	DataFusion is used to create modern, fast and efficient data
	pipelines, ETL processes, and database systems, which need the
	performance of Rust and Apache Arrow and want to provide their users
	the convenience of an SQL interface or a DataFrame API.

	## Why DataFusion?

	- _High Performance_: Leveraging Rust and Arrow's memory model, DataFusion is very fast.
	- _Easy to Connect_: Being part of the Apache Arrow ecosystem (Arrow, Parquet and Flight), DataFusion works well with the rest of the big data ecosystem
	- _Easy to Embed_: Allowing extension at almost any point in its design, DataFusion can be tailored for your specific usecase
	- _High Quality_: Extensively tested, both by itself and with the rest of the Arrow ecosystem, DataFusion can be used as the foundation for production systems.