Peloton is a self-driving database system with a new architecture that is designed for autonomous operation. Unlike earlier attempts in system tuning that only optimize the system for the current workload, Peloton predicts future workload trends and prepares itself accordingly. With this design, it can support all of the traditional system tuning techniques without requiring a human to determine the right way and proper time to deploy them. It also enables new optimizations that are important for modern high-performance DBMSs, but which are not possible today because the complexity of managing these systems has surpassed the abilities of human experts.

Source Code: Peloton is actively being developed and serves as my primary research platform. This page contains a full listing of contributors.


SQLCheck automates the detection of common SQL anti-patterns.

Source Code: SQLCheck is under active development.


PostgreSQL-CPP is a port of the PostgreSQL Database Management System to the C++ language (C++11 standard). We used it for bootstrapping the Peloton project.

Source Code: PostgreSQL-CPP spawned an interesting conversation and subsequent porting effort on the PostgreSQL hackers mailing list.


N-Store is a lightweight DBMS to evaluate different NVM-aware storage engines for transaction processing workloads. This project was subsumed into the Peloton project.

Source Code: N-Store is included as a part of Wisconsin's WHISPER benchmark suite for emerging non-volatile memory technologies.