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diff --git a/pg_lakehouse/Cargo.lock b/pg_lakehouse/Cargo.lock
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 Today, a vast amount of non-operational data — events, metrics, historical snapshots, vendor data, etc. — is ingested into data lakes like S3. Querying this data by moving it into a cloud data warehouse or operating a new query engine is expensive and time consuming. The goal of `pg_lakehouse` is to enable this data to be queried directly from Postgres. This eliminates the need for new infrastructure, loss of data freshness, data movement, and non-Postgres dialects of other query engines.
 
-`pg_lakehouse` uses the foreign data wrapper (FDW) API to connect to any object store or table format and the executor hook API to push queries to DataFusion. While other FDWs over object stores like S3 have existed in the Postgres extension ecosystem, these FDWs lack support for most object stores and table formats and are very slow for large analytical workloads. `pg_lakehouse` differentiates itself by supporting a wide breadth of stores and formats and by being very fast.
+`pg_lakehouse` uses the foreign data wrapper (FDW) API to connect to any object store or table format and the executor hook API to push queries to DataFusion. While other FDWs like `aws_s3` have existed in the Postgres extension ecosystem, these FDWs lack support for most object stores, file, and table formats and are very slow for large analytical queries. `pg_lakehouse` differentiates itself by supporting a wide breadth of stores and formats and by being very fast.
 
 ## Getting Started