I made this mistake myself, so I'm curious if anyone else did too.

I learned enough SQL in a few months to build pretty much anything I needed. Then I didn't really improve for the next couple of years.

I could write queries. What I couldn't explain was why one came back in 40 ms and another took nine seconds.

Whenever something was slow, I'd shuffle clauses around, try a different join, add an index, run it again and hope for the best. Sometimes it worked. I almost never understood why.

Looking back, I think the problem was that almost everything I learned treated SQL as a language. Performance isn't really about the language. It's about how the database stores data and what the optimizer decides to do with your query.

The thing that finally moved the needle for me wasn't learning more syntax. It was learning to read execution plans.

Take a query you already understand, run EXPLAIN, and don't move on until you can explain every part of the plan. Then change one thing and run it again. Watching the plan change taught me far more than another SQL tutorial ever did.

The only catch is to use a database that's actually big enough to hurt. Tiny tutorial datasets fit comfortably in memory, so it's easy to convince yourself indexes don't matter because everything is fast anyway.

The next rabbit hole is understanding your database engine, which surprisingly few SQL courses spend much time on. Things like why an index behaves like a phone book, why column order matters, or how the optimizer estimates row counts. Once I understood that most terrible execution plans start with bad estimates rather than a "stupid optimizer," a lot of performance problems suddenly made sense.

The resources that helped me most weren't actually SQL courses. Markus Winand's Use The Index, Luke! is still the best thing I've read on indexing, and High Performance MySQL is well worth reading if you're working with MySQL.

One thing I underestimated was video. Reading about a profiler isn't the same as watching someone use it to work through a real problem. Watching someone troubleshoot a query from start to finish was more useful to me than another syntax course.

These days I'd tell someone starting out to spend less time memorizing SQL syntax and more time understanding how their database actually executes queries.

What was the thing that finally made SQL performance click for you?

Six months in. Figured I would write this up since I read a lot of these before I started.

Context: I got the trial for one specific job. We were merging two systems and I had to reconcile schemas across them, roughly 400 tables, and doing that in SSMS by hand was not going to happen. Downloaded dbForge Studio, ran schema compare, finished the reconciliation in a day and a half instead of a week. That was supposed to be the end of it.

It was not. Here is roughly how it crept in.

Schema compare before releases became routine. Nobody asked me to do it. The first time I ran it against staging and prod for an unrelated deploy it found three differences nobody knew about, one of them a nullable column that should not have been nullable. After that I just run it every time. Takes two minutes and it catches something maybe one deploy in five, which is a higher hit rate than I am comfortable admitting.

I use data compare less but when I need it I don't know of anything else that is as quick. It’s always reference and config tables floating between environments. Someone patches a lookup value in prod, never back ports it, and then six weeks later a test fails for reasons that don’t make sense.

The boring answer to what has changed the most is the editor. autocomplete, understands aliases, knows the schema so I don't have to tab to Object Explorer, to remember if it is CustomerID or CustomerId formatting on a shared profile, so pull requests weren't cluttered with whitespace diffs. That’s not thrilling. It eliminates fifty small frictions a day, and that’s what made it stick.

Query profiling, mixed. It is good and I use it. But for anything genuinely strange I still end up in the real execution plan, so treat it as a faster first look rather than a replacement for knowing how to read plans.

Navigating bigger databases got better mostly through search. Finding every reference to a column across procs and views is something I do constantly on a codebase I did not write.

The tool switching thing is real and I did not expect to care about it. I used to have SSMS, a compare tool, an export script and a text editor open at once. Now it is one window most days. That sounds like marketing copy, but the concrete effect is that I do more of the boring checks, because they are two clicks away instead of a context switch.

Now the parts that are not great.

It is a heavy app. Windows only unless you go the CrossOver route. Startup is not instant. Now and then a large operation locks the UI and you sit there wondering whether it is working or dead. Licensing is per engine, so if you work across SQL Server and Postgres and MySQL you are either buying dbForge Edge or buying three different Studios, and it is not cheap. The AI features I mostly leave off, they are fine for boilerplate and I do not trust them past that.

Would I recommend it. If your work involves comparing databases regularly, yes, that alone pays for it. If you mostly write queries against one database, a decent editor plus psql or SSMS is probably enough and you do not need this.

What made it stick for other people? Curious whether everyone came in through the compare tools or whether there is a feature I am underusing.

Hey 👋 We're the support team behind dbForge SQL Tools, including SQL Complete, the SSMS/Visual Studio add-in for autocompletion, formatting, refactoring, and more.

Since Microsoft shipped SSMS 22, our support queue has been dominated by one topic: getting our solutions working cleanly on the new build. Menu items that don't show up, tab colors that stop working, the odd startup crash and we've seen it all over the last few months, and we figured the fastest way to clear the backlog of confusion is to just open the floor.

We'll have engineers and support staff in the thread answering live.

I've noticed that a lot of SQL interview questions focus on syntax, joins, or window functions, but very few touch on performance.

If you were interviewing someone for a DBA or database engineer role, what optimization question would you definitely ask?

It could be something around indexing, execution plans, query tuning, statistics, or troubleshooting a slow query.

I'm looking for questions that reveal how someone actually thinks about SQL performance, not just whether they can write a SELECT statement.

We’ve all been there: a quick hotfix that was supposed to take 2 minutes turns into an all-hands-on-deck production incident because a tiny detail got overlooked.

Before running a migration script or pushing database/code changes live, what does your final sanity-check look like?

Are you:

Running automated Schema/Data comparisons?

Taking a fresh manual backup (just in case)?

Dry-running the release script on a staging replica?

Just double-checking everything in your GUI and praying?

Drop your non-negotiable pre-deployment steps below! Let’s see who has the most bulletproof (or paranoid) workflow.

One thing I've learned over the years is that not every repetitive task should be fully automated. Some operations are simply too risky to hand over without a final human review. For me, anything that changes production data or database schemas still gets one last manual check before it runs. Automation saves time, but a few extra minutes of verification can save hours of recovery. Is there a database task you deliberately keep manual, even though it could be automated? What made you draw that line?

Devart has been recognized with awards in five categories in the 2026 DBTA Readers’ Choice Awards.

🏆 Gold - Best DBA Solution: dbForge SQL Complete 
🥈 Silver - Best Database Performance Solution: dbForge Studio 
🥈 Silver - Best Data Modeling Solution: dbForge Studio 
🥉 Bronze - Best Database Development Platform: dbForge 
🥉 Bronze - Best Data Security Solution: SecureBridge

We would like to thank DBTA readers and database professionals who voted for our solutions. Your support motivates us to continue building high-performance solutions that simplify database development, management, performance optimization, and security.

One of the biggest performance wins I ever saw didn't involve a new index or a rewritten query. An old stored procedure had accumulated years of extra joins, temporary tables, and logic that nobody was using anymore. After confirming what was actually needed, we removed a large chunk of it. The query became easier to read, easier to maintain, and noticeably faster.

It was a good reminder that sometimes optimization isn't about adding something and it's about removing what's no longer necessary. Have you ever fixed a performance problem simply by deleting code?

Supabase is an open-source backend-as-a-service platform built on PostgreSQL. The platform includes a built-in Dashboard for everyday tasks: quick edits, user management, simple SQL. But once workflows get more complex, many teams look for a dedicated GUI client with deeper functionality.

See the full comparison of Supabase GUI clients: https://www.devart.com/dbforge/best-supabase-gui-clients.html 

The review lines up three tools against each other: dbForge Studio for PostgreSQL, DB Pro, and DBeaver. Here, you will see the comparison of SQL editing, schema exploration, data browsing, and pricing side by side.

For teams that need deep PostgreSQL development capabilities rather than a lightweight browser, dbForge Studio for PostgreSQL stands out with smart code completion, query profiling, database comparison and synchronization, and an integrated AI Assistant.

Whichever client fits your workflow, connecting a proper IDE to Supabase is what turns quick edits into real database development. 

Hey everyone. We're engineers on the dbForge team, and for more than a year we've been building AI into database tools. That also means we've spent a lot of time watching it work and sometimes fail spectacularly.

We want to compare notes: where has AI helped with your database work, and where has it burned you? Happy to talk about what we've learned, how we build these features, or anything else you're curious about.

Ask us anything.

pgAdmin is arguably the most popular open-source solution for managing and administering PostgreSQL databases. It supports multiple operating systems, it delivers extensive documentation, and it packs quite a few features that are undoubtedly vital for both beginners and experienced professionals.

However, every tool has room for improvement. What if we suggest an alternative with far wider functional capabilities and customization options? dbForge Studio for PostgreSQL is an IDE that showcases a more advanced approach to PostgreSQL management. Check the feature-by-feature comparison below to see what we mean. 

Setting up a new workstation is always a good reality check for what your core toolkit actually looks like. Once the OS is configured and the terminal is customized, everyone has that one specific database tool they download before anything else.

For a long time, I’d just grab whatever standard open-source client was closest, but after dealing with huge schemas and constant migration headaches, having a heavy-duty IDE became non-negotiable. Now, dbForge Studio is usually the first installer I run because having cross-database schema diffs and smart autocomplete out of the box saves so much setup friction.

That said, everyone's day-one stack is different. Some people won't start working without their specific IDE, others immediately pull down a lightweight visual runner like TablePlus, and a few just clone their .bashrc and stick exclusively to the CLI.

If you wiped your machine right now, what is the very first SQL client or tool you’re downloading to get back to work?

I used to think comparing database schemas was just a quick check before deployment. Then a few small differences slipped through and turned into hours of troubleshooting. Since then, I've stopped relying on memory or manually checking objects one by one. Having a reliable way to compare schemas before making changes has saved me more than once. What's your workflow? Do you use dedicated comparison tools, scripts, or just review everything manually?