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The following commit(s) were added to refs/heads/main by this push:
     new 89a9c9087 docs: Add DataFusion Comet to Users section of README (#2283)
89a9c9087 is described below

commit 89a9c9087d9c506e064f818abd37d4bcc9bc8a70
Author: Matt Butrovich <[email protected]>
AuthorDate: Tue Mar 24 14:25:44 2026 -0400

    docs: Add DataFusion Comet to Users section of README (#2283)
    
    ## Which issue does this PR close?
    
    <!--
    We generally require a GitHub issue to be filed for all bug fixes and
    enhancements and this helps us generate change logs for our releases.
    You can link an issue to this PR using the GitHub syntax. For example
    `Closes #123` indicates that this PR will close issue #123.
    -->
    
    - N/A.
    
    ## What changes are included in this PR?
    
    <!--
    Provide a summary of the modifications in this PR. List the main changes
    such as new features, bug fixes, refactoring, or any other updates.
    -->
    
    - Add DataFusion Comet to the list of users with a description.
    
    ## Are these changes tested?
    
    <!--
    Specify what test covers (unit test, integration test, etc.).
    
    If tests are not included in your PR, please explain why (for example,
    are they covered by existing tests)?
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    - N/A.
---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index 20d3b11d8..4839a855c 100644
--- a/README.md
+++ b/README.md
@@ -133,6 +133,7 @@ The Apache Iceberg community is built on the principles 
described in the [Apache
 - [RisingWave](https://github.com/risingwavelabs/risingwave): A 
Postgres-compatible SQL database designed for real-time event streaming data 
processing, analysis, and management.
 - [Wrappers](https://github.com/supabase/wrappers): Postgres Foreign Data 
Wrapper development framework in Rust.
 - [ETL](https://github.com/supabase/etl): Stream your Postgres data anywhere 
in real-time.
+- [Apache DataFusion Comet](https://github.com/apache/datafusion-comet): 
High-performance accelerator for Apache Spark, built on top of the powerful 
Apache DataFusion query engine.
 
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