Query

Zerve simplifies data access by removing the need for matching driver packages in Python, streamlining workflows for data manipulation and analysis. It supports native SQL query execution, GraphQL for vector database, and database connectivity through Query Blocks, allowing users to execute queries and save the results in a dataframe for use in subsequent operations.

SQL On Pandas Dataframe:

Zerve supports utilizing any pandas dataframe as a database source, enabling the execution of SQL queries directly on the dataframe. To leverage this feature, connect a Python block containing a dataframe to an SQL block.

This integration allows you to perform SQL queries on the dataframe as if it were a traditional database, enhancing data manipulation and analysis capabilities within Zerve.