

RDST (Readyset Diagnostic & SQL Toolkit) is a free desktop app that connects to your Postgres database, ranks the queries actually costing you time, and explains what to do about each one.

The reason I built it is that the tooling Postgres already gives you is genuinely good, but addressing database performance issues is still a highly repetitive process:  
 

* pull pg\_stat\_statements and sort by total time
* take the top query and run EXPLAIN ANALYZE on it
* go find the table definitions for whatever it touches
* check whether the statistics on those columns are current
* work out whether the index you have in mind already exists under another name
* decide whether it is worth adding
* do it again for the next query

RDST collapses all of that into one pass, so instead of starting at step one you start at the answer.

Full disclosure - I work for Readyset (which is a caching layer for postgres / mysql), and this tool spawned from a recurring question our caching customers kept asking - which queries *should* we actually cache? And these same queries are the ones that, even without a caching solution, could heavily benefit from all the relevant performance diagnostics.  

RDST not only helps you discover slow queries and give you the appropriate action plan to improve them, but also provides full re-write suggestions, the ability to benchmark slow queries and track their  performance over time, and even allows you to ask any question about your database/queries in plain english and get helpful responses.

The tool is completely free to use, and we provide free trial tokens for all of the AI powered features. The app is in beta and we plan to release it under an MIT license. It runs locally, stores locally, and everything it does is read-only.  Full privacy related details can be found here: [https://readyset.io/docs/readyset-ai/rdst/desktop/privacy](https://readyset.io/docs/readyset-ai/rdst/desktop/privacy)

We would love feedback from people who actually spend time wrestling with queries every single day! Particularly:

* Does it surface the queries you'd investigate first?
* Are its explanations and recommendations useful, or merely confident-sounding database fan fiction?
* Would you be comfortable connecting it to a real environment? If not, what would stop you?
* What's missing from the workflow?

Source:  
[https://readyset.io/docs/readyset-ai/rdst/desktop](https://readyset.io/docs/readyset-ai/rdst/desktop)  
[https://github.com/readysettech/rdst](https://github.com/readysettech/rdst)



I built a free tool that does the pg_stat_statements to EXPLAIN to index recommendation loop for you