alamb commented on code in PR #294:
URL: https://github.com/apache/arrow-site/pull/294#discussion_r1065816100
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_posts/2023-01-07-datafusion-16.0.0.md:
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+---
+layout: post
+title: "Apache Arrow DataFusion 16.0.0 Project Update"
+date: "2023-01-07 00:00:00"
+author: pmc
+categories: [release]
+---
+<!--
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+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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+{% endcomment %}
+-->
+
+# Introduction
+
+[DataFusion](https://arrow.apache.org/datafusion/) is an extensible
+query execution framework, written in [Rust](https://www.rust-lang.org/),
+that uses [Apache Arrow](https://arrow.apache.org) as its
+in-memory format. It is targeted primarily at developers creating data
+intensive analytics, and offers mature
+[SQL support](https://arrow.apache.org/datafusion/user-guide/sql/index.html),
+a DataFrame API, and many extension points.
+
+DataFusion based systems perform very well on performance
+benchmarks, especially considering they operate on data in parquet
+files directly rather than first loading into a specialized format.
+Some recent highlights include [clickbench](https://benchmark.clickhouse.com/)
+and the [Cloudfuse.io standalone query
engines](https://www.cloudfuse.io/dashboards/standalone-engines) page.
+
+DataFusion is part of a longer term trend, articulated clearly by [Andy
Pavlo](http://www.cs.cmu.edu/~pavlo/) in his
+[2022 Databases
Retrospective](https://ottertune.com/blog/2022-databases-retrospective/).
+Database frameworks are proliferating and it is likely that all OLAP DBMSs and
other many data heavy applications such as machine learning, will require a
vectorized, highly performant query
+engine in the next 5 years to remain relevant.
+The only practical way to make such technology so widely available
+without many millions of dollars of investment is
+though open source engine such as DataFusion or
[Velox](https://github.com/facebookincubator/velox).
+
+The rest of this post describes the improvements made to DataFusion
+over the last three months and some hints of where we are heading.
+
+## Community Growth
+
+The three months since [our last
update](https://arrow.apache.org/blog/2022/10/25/datafusion-13.0.0/) again saw
significant growth in the DataFusion.
+TODO quantify the growth -- e.g. XXX new contributors to the project and
regularly merge YYY PRs a day.
+
+Growth of new systems based on as the engine in [many open source and
commercial projects](https://github.com/apache/arrow-datafusion#known-uses) and
was one of the early open source projects to provide this capability.
+
+Several new databases built on datafusion (synnada.ai, greptimedb, probably
others)
Review Comment:
Thanks -- added in ffe2e0af210. Still needs polish
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