This directory contains benchmark scripts for testing the performance of various database operations using pyodbc and mssql_python. The goal is to evaluate and compare the performance of these libraries for common database operations.

• To measure the efficiency of pyodbc and mssql_python in handling database operations.
• To identify performance bottlenecks and optimize database interactions.
• To ensure the reliability and scalability of the libraries under different workloads.

1. Set Up the Environment Variable:

   • Ensure you have a running SQL Server instance.
   • Set the DB_CONNECTION_STRING environment variable with the connection string to your database. For example:

     set DB_CONNECTION_STRING=Server=your_server;Database=your_database;UID=your_user;PWD=your_password;

2. Install Richbench - Benchmarking Tool:

   • Install richbench :

     pip install richbench

3. Run the Benchmarks:

   • Execute richbench from the parent folder (mssql-python) :

     richbench benchmarks

     Results will be displayed in the terminal with detailed performance metrics.

• Comprehensive Benchmarks: Includes SELECT, INSERT, UPDATE, DELETE, complex queries, stored procedures, and transaction handling.
• Error Handling: Each benchmark function is wrapped with error handling to ensure smooth execution.
• Progress Messages: Clear progress messages are printed during execution for better visibility.
• Automated Setup and Cleanup: The script automatically sets up and cleans up the database environment before and after the benchmarks.

• Ensure the database user has the necessary permissions to create and drop tables and stored procedures.
• The script uses permanent tables prefixed with perfbenchmark_ for benchmarking purposes.
• A stored procedure named perfbenchmark_stored_procedure is created and used during the benchmarks.