SQL Performance Cheatsheet — Queries That Scale: the $16 reference for developers whose queries choke at 1M rows
Your endpoint is fast in staging, then turns into a 4-second page load the moment real users start filtering, sorting, and paginating. That gap usually isn’t a missing index—it’s a missing mental model for how the database actually executes SQL. SQL Performance Cheatsheet — Queries That Scale is a $16, 26-page PDF from Yusuf Seyitoğlu that tries to close that gap with EXPLAIN analysis, index patterns, slow-query fixes, and database-specific deep dives. If you’re the developer who keeps asking why the query is still slow after adding an index, this is the kind of compact reference that can turn guesswork into a repeatable debugging path. It’s especially useful if you need to explain query optimization in an interview, rescue a slow report, or stop shipping pagination that falls over at depth.
Quick answer
| Best for | Developers debugging slow SELECTs, designing indexes, or prepping for database interview questions. |
| Skip if | You only need beginner SQL syntax, use a different database, or want a full video course. |
| Price | $16 |
| Format | 26-page PDF for PostgreSQL 14+ and MySQL 8.0+ |
| One-line take | A compact, production-minded reference that turns EXPLAIN output into actionable fixes. |
If that still sounds like you, the $16 SQL Performance Cheatsheet checkout is the fastest way to see what lands in your downloads folder.
What you’re actually buying
At $16, the value is simple: you’re not buying a long video course or a vague collection of best practices. You’re buying a compact reference that maps the usual suspects—bad pagination, unbounded SELECTs, functions on indexed columns, missing foreign-key indexes—onto the execution-plan evidence that proves why they hurt. That matters because most SQL performance work isn’t about writing fancier queries; it’s about reading the plan, spotting the expensive node, and applying a fix you can defend in code review.
The strongest part of the product is how the pieces connect. The EXPLAIN and execution-plan section gives you the diagnostic language, while the slow-query before/after patterns turn that language into practical rewrites. You also get index guidance that goes beyond “add an index,” covering B-tree, GIN, partial, and covering indexes, plus the column-ordering mistakes that make a perfectly reasonable index underperform. For teams running both engines, the PostgreSQL and MySQL deep dives keep the advice engine-specific instead of pretending one optimizer behaves like the other.
The quick-reference tables are the kind of thing you’d want pinned next to your terminal: an index decision matrix, an EXPLAIN node cheat sheet, and connection-pool sizing guidance. If your bottleneck is a report that takes 3 seconds, a list endpoint that gets slower on page 100, or an ORM that quietly issues hundreds of queries, this is a small, focused stack that can shorten the distance between “it’s slow” and “here’s the fix.”
Why it’s on our radar
The public page shows about 12 ratings averaging 4.9/5 and roughly 14 visible sales. That’s a small but credible signal for a $16 reference, especially in a space where developers are usually skeptical of quick-fix content.
What actually matters
- Database fit: It targets PostgreSQL 14+ and MySQL 8.0+. If your stack is older, or you’re working in SQLite, Oracle, or SQL Server, the general EXPLAIN habits may still help, but the deep dives won’t be your primary path.
- Level fit: It’s aimed at intermediate to advanced developers. If you’re still learning basic SELECT, JOIN, and WHERE syntax, you may find it dense. If you can already write working queries and just need to make them fast, it’s a better match.
- Your actual bottleneck: The slow-query patterns are most useful when you have a specific pain: N+1 ORM queries, deep OFFSET pagination, LIKE ‘%wildcard%’ searches, correlated subqueries, or unbounded result sets. If your problem is mainly application architecture or missing caching, this won’t replace that work.
- Interview prep: If you’re preparing to explain query optimization, focus on the EXPLAIN, join optimization, and index sections first. They’re the parts that turn a generic “indexes help” answer into a structured explanation of what the planner is doing.
Mid-check
If the slow-query patterns match your current project, View on Gumroad is the quickest way to compare the live price and download details.
FAQ
Is this a video course or a project-based course?
No. It’s a 26-page PDF you can open, skim, and apply while debugging.
Does it cover both PostgreSQL and MySQL?
Yes. It targets PostgreSQL 14+ and MySQL 8.0+, with separate deep dives for each engine.
Will it fix every slow query?
It won’t magically fix every workload, but it gives you a repeatable path: read the plan, identify the expensive operation, apply the matching pattern, and re-check the result.
What’s the download like?
It’s an instant-download PDF, listed at 26 pages and about 81.6 KB. The 26-page SQL Performance Cheatsheet PDF is small enough to keep open beside your editor.
Bottom line
If your queries work but don’t scale, this is a cheap, focused way to get a better mental model. It’s not a substitute for profiling your own database, but it gives you the vocabulary and patterns to move faster when a query plan looks ugly. If you’ve been adding indexes on instinct or rewriting pagination without a clear reason, the $16 price is easy to justify if you fix one production query.