The breakdown and prioritization by estimated time-saving potential is great. We run a multi-service application with several PostgreSQL databases, and as our data has grown, query performance has become more important. As a non-expert in DB optimization, pgMustard has done a great job boiling down the large amount of info Postgres gives you into genuinely useful visualizations.

@michristofides Btw, I am a fan of @pgMustard. Awesome software, helped me couple of times before.

Have you tried pgMustard? It's great for quick query optimisation

Learnings: ✅ Postgres has all you need ✅ FKs are not fast(er) out-of-the-box ✅ measure before *and* after adding an index! You can't just slap an index on every column. It may not help at all, or worse, make things slower! ✅ @pgMustard is great 😊

I have nothing but good things to say about pgMustard. They implemented a nontrivial feature in days and it is exactly what I asked for. I was able to delete and simplify my code without reworking it. Amazing work. cc @samuel_colvin twitter.com/pgMustard/status/1763103511951065374

@tobias_petry @IndexingBook @pgMustard Yes, I've used all of them and pgMustard is great. I still like to know all the details of the workings of the plan 😃

I was struggling with some slow DB queries and ChatGPT wasn't much help I'm now using @pgMustard with Django Debug Toolbar and have a much better idea at what steps to take to speed things up Great work @michristofides 👏

PG Mustard is a great tool, well worth the very cheap cost for a year. #PostgreSQL

✍️ New post covering a situation where I disabled the #PostgreSQL JIT to speed up some queries in a #Django project. @pgMustard was very useful for discovering the problem and giving advice! adamj.eu/tech/2023/11/09/django-disable-postgresql-jit

Part 1 #PostgreSQL query optimization. Started at 20s. Analyzed query plan + all tables/fields/conditions. Created around 10 hypothetical indexes, single and multi. Iterated w/ @pgMustard plans. Most plan nodes now index scans or index only scans. No query changes. Down to 3s.

I tried it and found it VERY helpful, thanks - I'm sure I'm still missing some opportunities but what I understood from it was enough to bring the problem query down to a manageable time (2s vs 12s). Even more importantly; I can now explain to my colleagues *what* is wrong, instead of "heeehh this is too slow" =)

Analyzing SQL performance can be hard. But, I found this website that could help read the analysis result better. Try it! - explain.depesz.com - app.pgmustard.com (paid service)

@_baretto @michristofides @pgMustard @pgMustard is a must have for me these days! I remember when @michristofides first took me through it i thought i might use it once a quarter but I've found myself using it far more frequently. Could not recommend it more!

If you are writing SQL queries for PostgreSQL you need to check out pgMustard. It's saved me several hours of debugging and optimization time. #sql #postgresql #performance

@pgMustard Your newsletter is so good! Always read the whole thing and that's pretty special considering the number of newsletters I subscribe to.

So much love for @pgMustard, found a missing index and went from ~700ms to ~15ms ❤️

@driscollis Software I install: Sublime Text Software someone else runs: @pgMustard

I really like the newsletter @michristofides is sending each month. He is curating so many good articles for each issue! I only read two (!) PostgreSQL newsletters, the other one is Postgres Weekly. That speaks for itself! pgmustard.com/newsletter

@tobias_petry @michristofides The pgMustard tool is also amazing. Wish it worked for MySQL too.