At ClickHouse, they appreciate open-source communities and the value they contribute to innovation. They have explored clickhouse-local – a version of ClickHouse designed and optimized for data analysis using local compute resources on laptops or workstations. This tool offers SQL query capabilities similar to a server installation but is available as a single executable binary. The Hugging Face API provides well-documented and consistent APIs, which has been fundamental in its adoption and position as the de facto means of sharing models and datasets. ClickHouse supports additional analytical functions to simplify queries, including correlation matrices, hypothesis testing, student t-tests, Welch t-tests, Cramer's V, and Theil's U. These statistical tests can be used to analyze the properties and distribution of data in a dataset, such as danceability, energy, popularity, and acousticness. Additionally, users can create user-defined functions (UDFs) to query Hugging Face datasets by only their name, making it easier to explore these large datasets on laptops or workstations. By using clickhouse-local, users can take advantage of the performance of ClickHouse while still being able to perform basic statistical analysis and data exploration without writing code in SQL.