diff --git a/README.md b/README.md
index ed7c121..38d7b70 100644
--- a/README.md
+++ b/README.md
@@ -12,7 +12,7 @@ UniverSQL relies on Snowflake and Polaris for access control and data catalog so
 * Snowflake SQL API implementation to handle the Snowflake connections, acting as a proxy between DuckDB and Snowflake.
   * You can connect UniverSQL using Snowflake Python Connector, Snowflake JDBC, ODBC or any other Snowflake client.
   * UniverSQL uses Snowflake Arrow integration to fetch the data from Snowflake and convert it to DuckDB relation.
-* [SQLGlot](https://sqlglot.com) for query translation from Snowflake to DuckDB,
+* [SQLGlot](https://sqlglot.com) and [Fakesnow](https://github.com/tekumara/fakesnow) for query translation from Snowflake to DuckDB,
 * [Snowflake Iceberg tables](https://docs.snowflake.com/en/user-guide/tables-iceberg) and [Polaris](https://other-docs.snowflake.com/en/polaris/overview) as data catalog, depending on `--account' you proxy to.
 * Your local disk for the storage with direct access to data lakes (S3, GCS) for the cloud storage.
 * [DuckDB](https://duckdb.org) as local compute engine.
diff --git a/pyproject.toml b/pyproject.toml
index dadd30d..8a82bb3 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -17,17 +17,13 @@ uvicorn = "^0.30.1"
 snowflake-connector-python = {extras = ["pandas", "secure-local-storage"], version = "^3.11.0"}
 eval-type-backport = "^0.2.0"
 pip-system-certs = "^4.0"
-chdb = "^1.4.1"
 fsspec = "^2024.6.1"
 gcsfs = "^2024.6.1"
 click = ">7"
-acryl-datahub = "^0.13.3.4"
 s3fs = "^2024.6.1"
-textual = "^0.74.0"
 pyiceberg = "^0.7.0"
 sqlalchemy = "^2.0.31"
 fastapi-utils = "^0.7.0"
-
 fakesnow = "^0.9.20"
 humanize = "^4.10.0"
 [tool.poetry.dev-dependencies]