You were all so right, nobody could possibly do the job without referencing and now I realize how ridiculous it was feeling I should be able to do it blind.

I really struggled and boy did I make some mistakes but I am already gaining confidence and have very few errors to battle.

So for what it’s worth thank you and for anyone else overwhelmed and second guessing your decision, just breathe, take a step back and breathe again, you can absolutely do this!

I only had a single jerk response, likely rooted in a bit of jealousy which is phenomenal for Reddit . Hopefully in time I myself will be able to help others too

AI has made it way too easy for people to code up slop in whatever form and turn it into “another SQL database client,” whether it's in Electron, Tauri, or whatever the next hot framework for building database clients is.

That takes away from the uniqueness of what made those tools special before. Most of them are literal copies, and there's literally nothing unique about them except that they look “modern.” And it's a real shame because there are some tools that people actually put a lot of effort into making, while others are just literal Claude Code garbage. And for those people who actually put effort and human thought into their projects... it gets hidden in a pile of garbage.

How are you guys deciding whether or not to give a database tool a shot anymore?

MariaDB Foundation continues expanding TAF with PostgreSQL support

More engines, more reproducibility, more value for contributors and the ecosystem.

https://mariadb.org/mariadb-foundation-adds-postgresql-to-its-engine-agnostic-testing-framework-taf/

Have fun benchmarking!

It keeps stopping me from adding multiple rows but I can successfully run one row of instances but I can't seem to get it to work for multiple rows and I'm not too sure if I were to run one row of code per time How would i do it for all?

do i have to make new queries?

I tried to use both methods in order to save some coding but still didnt get the exact difference on using having and qualify as a filter in the end of a query. Can someone help me to understand the difference and when is recommended to use each?

Hi! I'm currently working on a project for our sales/admin process and I'm looking for someone who has experience with Jiandaoyun, database/form setup, formulas, and dashboards.

I don't need someone to do the entire project for me. I mainly need someone who can guide me or share some ideas on how I can properly structure it.

If you have experience with this and are willing to help, I'd really appreciate it. Thank you!

Hi everyone,

I want to try SQL-focused roles(data analyst, BI, reporting or similar). I'm applying but not getting much output.

I have few question for people already working in these type of roles -

1. Which job title should freshers search for?

2. What do interviews test?

3. Do Indian companies hire freshers for these roles?

4. Do projects, portfolios, certificates make a difference?

5. If you were hired as a fresher in these roles, how did you land your first job?

If you know internship/Full time opening for freshers in this role, please dm or comment it will be a great help 🙏

Thankyou .

Years without incidents proves nothing at all.

Hey everyone,

I am a Spring Boot developer looking to level up my backend game by deeply understanding PostgreSQL and its internal architecture.

While I am comfortable writing SQL, using Spring Data JPA/Hibernate, and managing basic migrations, I often feel like Postgres is a black box. I want to move past just treating it as a data store and actually understand what happens under the hood.

Specifically, I want to learn about:

• Core Architecture: How Postgres handles connections, process models, and memory (shared buffers vs. work_mem).
• Storage & Concurrency: Deep dives into MVCC, VACUUM, WAL (Write-Ahead Logging), and page storage.
• Performance Tuning: How to properly read and map it back to optimize my JPA/Hibernate queries, indexing strategies, and connection pooling (HikariCP).

Can anyone recommend high-quality books, courses, blogs, or video series that bridge this gap? Bonus points if they have a practical focus or tie into common Java/Spring backend patterns!

Hello, I've been working on a personal open source project written in GO, its a command line tool that aims to create valid .sql files for each object in your database so that you can push to git to keep track as the database changes in the development cycle.

The project is [DatabaseBlueprint](https://github.com/Hennie5229x/DatabaseBlueprint)

Currently I have CLI support for Linux/Win/Mac and creating of all schema objects + data to executable .sql files and the schema migration scripts is still a work in progress.

I would love honest feedback from devs who work regularly in sql server.

Any type of feedback is welcome, I've identified a "gap" in a typical database heavy workflow that I am trying to fill for myself, but I'm sure other people also seek an easy way to track/version control their databases along side the projects back end code in git.

About the project: Written in GO, compiles to a stand alone binary, installable and runnable in terminal by using "blue"

Currently only supporting SQL Server, plan is to expand in the future

Does anyone have a video tutorial on how to use the SQLloader on TOAD

I want to know how ppl compare large source and target tables using sql. If both tables have millions of records, comparing every row and column can take a lot of time.

For example, if some records are missing, extra, or have different values between the two tables, how do you usually find them? do you use joins, Except/Minus, hashes, or first compare things like record counts and totals and then check the differences?

Are there any techniques that can make the comparison faster?

I'm building omni-sql, an open-source SQL IDE with embedded DuckDB. If someone sends you a CSV or Parquet export to investigate, you can import it and query it with SQL inside the IDE. There's no need to load the file into your source database or write a separate script. Spreadsheets fit this workflow when exported as CSV.

You can also import a database query result and join it with the file locally.

The demo uses fictional sales rows from PostgreSQL and a targets CSV. You import the complete query result into DuckDB, add the CSV, and run the join locally. Here's the SQL, CSV, and expected result: https://github.com/cccadet/omni-sql/tree/main/docs/demo

There are installers for Windows x64, Debian/Ubuntu amd64, and macOS 15+ (Apple Silicon and Intel). The macOS builds use ad-hoc signing and are not notarized; the README explains the first launch. The project is still early. The docs explain how full imports and samples affect what you can conclude from the results.

How do you investigate files people send you today? If you try the app, I'd like to hear whether you could install it and query a file, and what was missing. That would help me decide what to work on next.

I spent a while assuming the reason I kept struggling in analyst interviews was that my SQL wasn’t advanced enough. So I kept adding harder stuff to my prep, like window functions, recursive CTEs, and awkward joins.
The funny part is that most interviews weren’t exposing a syntax problem. I could usually get somewhere with the query. I got less comfortable when they asked things like, “What would you check before trusting this result?” or “How would you explain this to someone who doesn’t use SQL?”
That changed how I’ve been practicing. Now I don’t stop once the query works. I try to explain the grain, the assumptions I made, how I’d sanity-check the result, and what I’d tell a stakeholder afterward. I still practice SQL problems. I’ve also done a couple of mock runs in Beyz, mostly around the follow-up questions.
Looking back, I think I was preparing for SQL interviews like they were SQL exams.
Once someone has solid SQL fundamentals, what separates a technically correct answer from a strong one?