The Self-Driving Database Management System
The Peloton project is dead. We have abandoned this repository and moved on to build a new DBMS. There are a several engineering techniques and designs that we learned from this first system on how to support autonomous operations that we are doing a much better job at implementing in the second system.
We will not accept pull requests for this repository. We will also not respond to questions or problems that you may have with running with this software.
We will announce the new system later in 2019.
During last two decades, researchers and vendors have built advisory tools to assist database administrators in system tuning and physical design. This work is incomplete because they still require the final decisions on changes in the database, and are reactionary measures that fix problems after they occur.
A new architecture is needed for a truly “self-driving” database management system (DBMS) which is designed for autonomous operations. This is different than earlier attempts because all aspects of the system are controlled by an integrated planning component. In addition to optimizing the system for the current workload, it predicts future workload trends which lets the system prepare itself accordingly. This eliminates the requirement of a human to determine the right way, and reduces time taken to deploy the changes, optimizing the DBMS to provide high-performance. Auto-management of these systems has surpassed the abilities of human experts.
Peloton is a relational database management system designed for fully autonomous optimization of hybrid workloads. See the peloton wiki for more information.
Check out the installation instructions.
The Wiki also contains a list of supported platforms.
We invite you to help us build the future of self-driving DBMSs. Please look up the contributing guide for details.
Before reporting a problem, please check how to file an issue guide.
Technology preview: currently unsupported, possibly due to incomplete functionality or unsuitability for production use.
See the people page for the full listing of contributors.
Copyright © 2014-2018 CMU Database Group
Licensed under the Apache License.