Pick one. You can only use it for the rest of your career: SQL or Python? I'll go first: SQL. Not because it's better. Because every company I've walked into — from startups to enterprise — the first thing anyone asks is "can you write a query?" But here's the thing most people miss: SQL isn't just a query language. It's the language of data architecture. Every table you design, every join you write, every view that powers a dashboard — you're making architectural decisions. You're defining how data lives, moves, and gets consumed. Python opens doors. SQL keeps you in the room. Data architects think in systems. SQL is how you speak that language fluently. #DataEngineering #SQL #Python #DataArchitecture #TechCareer
Given that you can write Python that generates SQL and not vice versa, I'd probably go with Python.
SQL have evolved from set definitions into a set-based procedural language. Python interpreters, despite their increasing sophistication and versatility, are still far less robust and lack the speed of SQL engines when acting on large data sets. I suspect that AI's heavy Python centric data manipulation models are the reason why AI reliability degrades sharply as the number of "tokens" and the "token" value-ranges increase.
SQL is optimized for set-based operations inside the database. Python handles orchestration, integrations, and advanced logic. They’re complementary, not interchangeable. If you’re choosing one for life, you’re thinking about this the wrong way.
UNPOPULAR OPINION ALERT. Why not agentic AI and just let them code. Why must we choose side when the obvious choice is someone we can boss around whole day and making us feel productive instead of being real productive? Above was sarcasm. I’d go with Python—you can still use SQL within it via libraries like sqldf or SQLAlchemy, so you get both in one ecosystem.
SQL. Not close. Python is powerful, but SQL is how you define the relationships, the grain, the business logic that everything downstream depends on. A well-modeled star schema in SQL is the foundation that makes every Python script, every dashboard, and every ML model trustworthy. Python processes data. SQL architects it.
Why not both? I find a lot of analyst roles, engineering roles, and even business intelligence roles are starting to ask for both skills. Technology is always marching forward and personally having both in my skillset has been not only empowering in my work, but has shown massive efficiencies!
I’d agree with SQL, not because it’s better or something I've used much more heavily during my career than brief flirtations with Python, but because it underpins so much of how systems actually work. It’s where the data, logic, and structure all come together.
are the questions getting smarter and smarter or I am getting dummy and dummier. how SQL can VS. Python?
SQL has been putting food on my table for at least 28 years. I don't feel like it is going anywhere. Doesn't feel like schools are concentrating on relational DB skills, and CoPilot can't seem to figure out what may or may not work with varying normal levels of permission in Azure SQL vs Desktop.