diff --git a/best_practices/datasets.md b/best_practices/datasets.md
index 93d4a9dd..0bb37797 100644
--- a/best_practices/datasets.md
+++ b/best_practices/datasets.md
@@ -47,7 +47,7 @@ SQLite is a transactional database, so if you have a dataset that is changing wi
   - Vaex is an alternative that focuses on out-of-core processing (larger than memory), and has some lazy evaluation capabilities.
 - Polars
    - An alternative to Pandas (started in 2020), which is primarily written in Rust.  Compared to pandas, it is multi-threaded and does lazy evaluation with query optimisation, so much more performant.  However since it is newer, documentation is not as complete.  It also allows you to write your own custom extensions in Rust.
-
+DataFusion is a very fast, extensible query engine for building high-quality data-centric systems in [Rust](http://rustlang.org/), using the [Apache Arrow](https://arrow.apache.org/) in-memory format. DataFusion offers SQL and Dataframe APIs, excellent [performance](https://benchmark.clickhouse.com/), built-in support for CSV, Parquet, JSON, and Avro, extensive customization, and a great community. More info [Apache Datafusion](https://datafusion.apache.org/)
 ## Distributed/multi-node data processing libraries
 - Dask
    - `dask.dataframe` and `dask.array` provides the same API as pandas and numpy respectively, making it easy to switch.