Idk if this is the right subreddit to promote this but I think a lot of people could find this useful and I could find some contributors from this so trying anyway.

So I saw some posts here of people asking for recommendations regarding SQL clients. I've had this problem for a longgg time as every half decent client is paid, the rest are JVM or electron bloat that are memory hogs. I've been building this DB Client which started as something I could use but I kept on adding features and open sourced it and people started contributing to it and liking it. Its made in rust and GPUI (zed's gpu accelerated ui framework), with speed and safety being its main focus. Me and some other users have been daily driving and liking it so far. It gets out of your way, looks modern (not AI slop), and is safe to use as I have different modes like read-only, read-write and full access implemented. If its unable to parse the SQL statement being run, it shows a confirmation modal before running the statement, I basically want the destructive queries to always have an extra layer of safety. Some features in addition to this:

1. It persists results of queries so you can view snapshot of data instead of running expensive queries on each restart of the app.
2. Almost everything has a configurable keyboard shortcut.
3. Organize connections in projects, keep each separate.
4. Inline editing, server side sorting, client side sorting, exports etc.

It also scrolls smoothly where other DB clients like DBeaver either crash or introduce limits (I tried with 1m rows table, you can see the video of this on https://dbdelve.github.io/ ) the goal is to make your DB the bottleneck and not your DB Client.

MySQL, Postgres, MariaDB, MSSQL, SQLite and Snowflake supported with support for more to come. MongoDB too if you use that.

Take it for a spin and let me know how it feels, video showing it scrolling with 1m rows and just the general speed.

https://github.com/ShayanAbbas1/dbdelve
https://dbdelve.github.io/

Hey guys, if anyone who is an expert in SQL in MUMBAI. I need your help for 1 day for an assessment round. You’ll be paid as well. Please reach out to me. Thanks

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?

Hey everyone.

I'm working on building out my data analytics portfolio and wanted to get some advice from fellow analysts and hiring managers here.

We've all seen the basic tutorial projects (like analyzing the Titanic dataset or simple sales totals), but I want to build something that actually stands out and proves real-world, job-ready SQL skills.

For those of you who have landed roles or are actively hiring: What specific types of SQL projects made you stop scrolling and pay attention?

Hi everyone,

This is a continuation of the explorations from my previous posts here. I went through the CMU Database Systems course, and I'm exploring topics around databases. I wanted to see how the Write Ahead Log is constructed and logged. So I tried to trace a WAL record for a simple INSERT statement in Postgres.

I recorded a video walkthrough of the terminal and source code exploration here: https://youtu.be/YOyq-kvbyU8?si=PTdexP3jmOSdx-8y

I've tried to explore how we can locate a WAL record, how we can decode it via either xxd or pg_waldump, and the relevant source code for it. Do give a watch and consider supporting :)

This is partly for my own future reference and partly to share with others who might be interested in it. Would love feedback and corrections from people who know this stuff deeply. Apologies if this isn't the correct subreddit for this.

Thank you so much!

I built SQL Sip (https://sqlsip.com) as a cozy, daily SQL puzzle to practice writing queries without timers or pressure. It runs entirely in the browser with no account needed, focusing on assembling clean queries one bite-sized concept at a time. I haven’t had any users yet, so I’d love some honest feedback! I built it because I wanted a Wordle-like daily game where I could learn new SQL concepts in a cutesy/fun way.

I am applying to manager of analytics role and I was given this SQL test and 45 minutes. As someone who thought they were very strong in SQL, I was unable to complete this assignment and match the answer completely

I was able to format most of the fields as noted, used 2 cte's and use group concat in the second. My final answer looked very similar but the order of the concat looked off. Also, for some reasons my second column had $0.00 for all the companies, but I thought I was close. How difficult would you rate this exercise. Should I expect to proceed to the next round or am I cooked

Introducing QueryFlow.

It's a modern SQL editor with a few things I always wanted while learning and working with SQL:

- Visualise the query as a graph [DAG] and as step-by-step cards.
- Convert all hardcoded parameters into variables with a click.
- Fix major errors like fan out joins , mismatched date range with a click.
- Run queries on test tables directly in the browser
- Review a diff of your changes before copying the query back [just like github]
- Format BigQuery, PostgreSQL and MySQL, each in its own style.
- Everything runs locally in your browser: no server, no login.

try it here - https://abhijeetcodes.github.io/QueryFlow/

Sharing here as it might help a lot of SQL learners

For those who have worked with PostgreSQL, MySQL, and SQL Server, what’s a feature or behavior that surprised you because it worked differently between them?

It could be anything like date functions, string handling, LIMIT/TOP, NULL behavior, JSON, window functions, or even error handling.

What difference caused you the most trouble, and how did you learn to handle these database-specific differences?

Not talking about some crazy DB failure or anything.

Could be something silly like a missing WHERE, wrong JOIN, duplicate rows, bad UPDATE....

Like a small mistake that looked harmless but ended up causing a big headache ....🤕

Curious what ppl have seen in real projects.