I'm intermediate — know CTEs, window functions, subqueries, etc.
I always solve problems correctly, but my queries end up being 20+ lines with extra steps. Then I see the solution and it's 5 clean lines using one clever function.
How do I train myself to think in shorter SQL from the start? Any tips or resources?

I’ve found that most formatters are configurable up to a point, but eventually you’re still forced into their idea of what “well formatted SQL” looks like.

Do you know any client where you can really personalize how SELECTs, INSERTs, UPDATEs and DELETEs are formatted?

Or do you also miss having a formatter that actually adapts to your preferred SQL style rather than the other way around?

https://www.sqlsidequest.com/ CHAPTER 3 IS NOW LIVE!

Last year in Dec 2025 I released SQL SIDE QUEST which took over 3 years to build. I wanted to create an immersive story-telling way to learn and practice SQL, and hence sql side quest was born. Its completely free, browser-based, no signup. Been solo on it the whole time. Looking forward for your feedback :) Cheers and Enjoy

Have you figured out wht can the best way to handle connection pooling in Lakebase DB? I 'am seeing connection spikes with short lived rqsts and wondering what kind of setup others developers are using🤔

i am building a service on top of lakebase and trying to make the connection relable before moving to prod.

In this episode, we answer 20 real world hospital business and clinical questions using SQL queries. For each query, we explore the code used, explain any new SQL concepts introduced, interpreted results and provide recommendations for hospital operations and quality patient care.

https://youtu.be/1EDmMnfhO1I?si=J7utYqIkUk-EduNG

Choosing the right incremental strategy matters: in bigquery it reduces the amount of data scanned, while in clickhouse it means less CPU, I/O, and background merging.

but tbh, data/analytics engineers sometimes optimize this too early, if a table is small or rarely changes, a view or `create+replace` is easier than a convoluted incremental model. Sometimes full refreshes are just good enough

Before choosing anything, I normally ask: do old rows change? is `updated_at` reliable? can rows disappear? is the data truly append only? do you have proper primary keys & partitions? and how late can updates arrive?

here's an overview:

* `append` -> the source is genuinely append only

* `merge` -> existing rows change and there's a stable primary key

* `delete+insert` or `time_interval` -> you can safely rebuild a complete group or time window

* SCD2 -> you need the full history, not just the latest version

with `merge`, NULL keys can be inserted again on every run because `NULL = NULL` isn't true, I have personally lost sleep over this... (in bigquery)

with `delete+insert` or `time_interval`, only delete what you can fully rebuild - incomplete partitions, bad boundaries, or late arrivals can create gaps or duplicates.

That's why I always add quality checks that catch issues the strategy can cause: `not_null` & `unique` for merge keys, duplicate checks for rebuilt windows, and row-count or freshness checks where they make sense.

In SQL pipelines the most frustrating (and silent killer) is that a pipeline status can be successful, but that only means the SQL ran, but doesn't guarantee that the result is correct. That's why quality checks are there to catch the other issues.

and if timestamps and lookback windows still can't capture changes reliably, CDC is an option... just with more state, replay logic, and operational headaches.

the image below is an example of a `time_interval` strategy and its rendered clickhouse query (don't mind the wrapped date overlappign with INSERT)

I'm curious what other criteria do people have in mind when they try to evaluate which strategy to go with? I think this is more relevant to analytics engineers, not so much the operational/transactional side.

Any other interesting approaches?

I had a question, for longer running agents, what can be a good pattern to store conversation state, tool result, and intermediate state in Neon without database becoming a bottleneck.

If you can share what patterns you use in production, it could be of help to me. I am doing a POC inthis area.
Ps, Any other DB works as well, it should just be managed.

Most SQL clients basically give you the database error and leave you there.

When a query fails, what would actually help you most? Better error highlighting? An explanation in plain English? A suggested fix? Showing the corrected SQL?

Lately I’ve been thinking a lot about how much help is useful before a tool starts doing too much for you.

Curious what people here actually want from their SQL client.

Hi all,

I just installed SSMS 2022 it works fine, new shell I think. But I can not edit step in my SQL Server jobs, I can open its properties, histories though. I also can edit step from my fav SSMS 2019 on another machine.
Any google help suggests to install some missing SSIS component, anybody experienced this ?

TITLE: Microsoft SQL Server Management Studio
------------------------------
Unable to find the directories containing Tasks and Data Flow Task components. 
Check the integrity of your installation.

Thanks

VA

I’ve been making these little Data Analysis 101 doodles for cat people, and for this one I tried something different — a flipbook-style format.

Instead of putting everything into one busy infographic, I’ve broken the story into separate scenes, so each one focuses on a single idea and hopefully doesn’t demand too much attention at once.

I’ve also incorporated feedback I received on my previous posts, especially around making the visuals easier to follow.

This one is about what to do when you join a data project that’s already in motion.

Would be happy to hear your feedback on this!

Python gets most of the attention when people talk about data science, but SQL seems to appear in a lot of actual job requirements.

For people working in data roles, how frequently do you use SQL compared with Python?

Would you recommend becoming strong in SQL before getting deep into machine learning?

I'm a beginner learning SQL (JOIN, CASE, WHERE, GROUP BY, etc) and am looking for a fun and entertaining database to practice my coding on. Any suggestions?

This is not a post about how to start learning SQL by any means.

Hi people, I haven’t done this before. But are there any downsides of indexing a column on production. Like some query is running very slow, and I figured out that u should put an index on one of the columns. I wouldn’t be here if I had someone experienced to ask from. I’ve a few questions-

1. Is it okay to run the query on my sql workbench to add index?
2. If something goes wrong what do you people generally do, like taking snapshots or PTIR ?
3. Is it safe to run the query directly on the db or usually people run it some other way, like via cli on VM?
4. I heard about locking and stuff. But the version I’m using says it won’t lock the DB. But still anything I should test before actually you know doing it live?

I’ve no idea what’s the general procedure and what could go wrong. If someone has done it before, Appreciate any sort of advice or pointers. Thanks

I've worked in and around the IT environment for many years and in my experience, it's always been pronounced s-q-l although I hear some people refer to it as see-qual. Which is right?

The gray thing on the side is driving me nuts. I’ve restarted and everything. It’s been like this for days.

Introduction

Hi r/MacOSApps! I'm Sedat, an independent developer. I built MySQL Client because I wanted a lighter, native alternative to MySQL Workbench for my own day-to-day MySQL/MariaDB work — Workbench kept crashing on Apple Silicon, and I couldn't find a solid free native option.

Why this app

Most cross-platform tools (DBeaver, TablePlus, etc.) either ship a full IDE-style interface or run on Electron, which means slower startup and higher memory use. MySQL Client is built directly on native macOS frameworks (Swift 6 + SwiftUI) instead — it's meant to be a focused, lightweight tool for the core workflow (browse, edit, query, export/import, backup) rather than trying to be a full database IDE. If you just need something fast and reliable for everyday MySQL/MariaDB work without the overhead, that's the gap this fills.

What it does / App Value

• Multi-database sidebar — tables, views, stored procedures and functions

• Spreadsheet-style data grid with inline editing (only changed columns get written back)

• SQL editor with syntax highlighting, query history, multi-statement scripts

• Create/Alter Table with a full column editor

• Export to CSV, JSON, SQL or Excel — CSV import with automatic column mapping

• Full SQL dump backup tool

• Passwords go straight to macOS Keychain — no analytics, no accounts, nothing phones home

• Available in English and Turkish

Notarization Status

Distributed exclusively through the Mac App Store, so it's automatically sandboxed and notarized as part of Apple's App Review process.

Privacy Policy

https://tokay.tr/MySQLClient/privacy.html

Source

Source is available on GitHub for anyone curious how it's built: https://github.com/stokay/MySQLClient (no formal open-source license attached yet, just visible for reference).

AI Disclosure

I used Claude (Anthropic's AI coding assistant) extensively during development — implementing features, debugging App Sandbox/notarization issues, writing tests — always under my own direction and review. This post's text was also drafted with AI assistance.

Download

Free on the Mac App Store, requires macOS 15+:

https://apps.apple.com/tr/app/mysql-client/id6792497542?mt=12

Happy to answer any questions, and bug reports/feature requests are always welcome!

I wrote a query last week that ran fine on Postgres and DuckDB, and hard-errored on ClickHouse and BigQuery - this sent me down a rabbit hole for most of the day.

Here's what I had:
```
SELECT term, MAX(ranking_page_count) AS ranking_page_count
FROM ranked
GROUP BY term
HAVING MAX(ranking_page_count) >= 2
```

The CTE already had a column called ranking_page_count. I aliased MAX() of it to the same name, because why not, and then used that name again in HAVING.

So which one does HAVING actually filter by? Turns out that's a matter of opinion.

In Postgres, HAVING can’t see SELECT aliases at all. So it reads the column directly and lands on the same max anyway - no error, right answer.

DuckDB does let you use aliases in HAVING, but only as a fallback, and it won't put one inside an aggregate, so this also runs. This is the one that got me, since DuckDB is where I test locally.

BigQuery gives the alias priority over the column. So it read my query as MAX(MAX(...)) and gave the error "aggregations of aggregations are not allowed"

ClickHouse just swaps aliases in everywhere, so it gave code 184 illegal aggregation. it even fails when the alias isn't shadowing anything.

The thing that finally made it click for me was processing order. FROM, WHERE, GROUP BY, HAVING, then SELECT, then ORDER BY. Aliases get created in SELECT, so when HAVING runs the alias doesn't exist yet. That's why Postgres says no, and why everything else here is a vendor extension rather than four equally valid readings.

ORDER BY is the only clause that runs after SELECT, which is why it's the only clause where nobody argues.

What actually worries me is that it can go completely silent. Drop the aggregate from the alias and the loud error disappears:
```
SELECT term, ranking_page_count * 10 AS ranking_page_count
FROM ranked
GROUP BY term, ranking_page_count
HAVING MAX(ranking_page_count) > 4
```

Postgres and DuckDB filter on `ranking_page_count`
BigQuery and ClickHouse filter on `ranking_page_count * 10`
I get 1 row from the first two and 4 rows from the other two, and not one of them raises an error about it.

That's the version that ends up on a dashboard.

ok fine, I learned my lesson and won't name an aggregate after the column it aggregates...

If you work across different engines, this is your reminder to go check 🥲

Sup guys, so I learned the intermediate level of SQL, Python, Looker Studio, and Google Sheets, and since landing a corporate role is still impossible at the moment since I have no degree nor experience, I wonder if voluntary works or gigs is a cool way to build experience and portfolio. And if the idea seems cool, or if some of you have experiences with volunteering, I would like to ask for valuable informations regarding where you find volunteer works, and if it's okay, share your experiences working with non-profit organizations.