One of the few things I have used in programming and technology consistently for over 25 years is SQL. Almost no time spent learning how to organize and query data has been a waste in my career.
The mere existence of Pandas makes me extremely grateful for SQL, because my job would be absolute hell if I had to use pandas or a similar syntax. It’s hard to overemphasize just how perfect SQL is for the job that it does.
I don't think SQL is "perfect" and I'm not sure it's rational to even be saying that. For instance, why is it that the syntax for an SQL query is "select A from B" when many SQL-inspired syntaxes have switched to something like "from B select A" to make it more compositional?
The relational model is pretty simple though. Pandas is an awful mess.
I've loved and used Django ORM and SQLAlchemy for many years. It got me a long way in my career. But at this point I've sworn-off using query-builders and ORMs. I just write real, hand-crafted SQL now. These "any db" abstractions just make for the worst query patterns. They're easy and map nicely to your application language, but they're really terrible unless you want to put in the effort to meta-program SQL using whatever constructs the builder library offers you. CTEs? Windows? Correlated subqueries? It's a lot. And they're always lazy, so you never really know when the N+1s are going to happen.
Just write SQL. I figured this out when I realized that my application was written in Rust, but really it was a Postgres application. I use PG-specific features extensively. My data, and database, are the core of everything that my application does, or will ever do. Why am I caring about some convenient abstractions to make it easier to work with in Rust, or Python, or whatever?
I love SQL and use it all day long to answer various business questions, but I would never use raw SQL in my code unless there is a good reason for it (sometimes there is). ORMs are there for maintainability, composability, type safety, migrations, etc.. trying to do all that with raw SQL strings doesn't scale in a large code base. You need something that IDE tools can understand and allow things like 'find all references', 'rename instances', compile time type checks, etc.. Raw SQL strings can't get you that. And managing thousands of raw SQL strings in a code base is not sustainable.
ORMs are one of those things that a lot of people think is a replacement for knowing SQL. Or that ORMs are used as a crutch. That has nothing to do with it. Very similar to how people here talked about TypeScript 10 years ago in a very dismissive way. Not really understanding its purpose. Most people haven't used something like Entity Framework either which is game changing level ORM. Massive productivity boost, and LINQ rivals SQL itself in that you can write very small yet powerful queries equivalent to much more complex and powerful SQL.
No issue at all. There is a place for stored procs and functions in cases where you need to do things an ORM is not capable of. It is an exception, not a rule. Managing procs/functions is overhead and has the same if not more maintenance headaches than raw SQL strings in code.
I'm curious if you have tried SeaORM? I've used it a little bit (not too extensively) and really like it. It's like sqlalchemy in that you can declare your tables and have a type checked query builder, which is a big win IMO. It's nice to add/change a field and have the compiler tell you everywhere you need to fix things.
I've definitely had issues when using sqlalchemy where some REST API type returns an ORM object that ends up performing many queries to pull in a bunch of unnecessary data. I think this is harder to do accidentally with SeaORM because the Rust type system makes hiding queries and connections harder.
Most of my usage of SeaORM has been as a type query builder, which is really what I want from an ORM. I don't want to have to deal with lining my "?" or "$1" binds or manually manipulate strings to build a query. IMO a good query builder moves the experience closer to writing actual SQL, without a query builder I find myself writing "scripts" to write SQL.
You may not need to use an ORM, but hand writing SQL, especially CRUD, should be a terminable offense. You _cannot_ write it better than a process that generates it.
SQL has been the main skill I have relied upon my entire career. Yes, I have worked with Pandas and other data libraries; my take away from working with Pandas is it is a pretty language but obfuscates the relational database with a non-relational lanuguage. Relational databases require a relational language which is what SQL is.
Somewhat tangential to the article, but why is SQL considered a programming language?
I understand that's the convention according to the IEEE and Wikipedia [1], but the name itself - Structured Query Language - reveals that its purpose is limited by design. It's a computer language [2] for sure, but why programming?
"structured query language" is actually a backronym, SEQUEL is indeed a programming language and the only mainstream 4GL. consider the output of the compiler (query planner) is a program with specific behavior, just that your sql code is not the only source - the other inputs are the schema and its constraints and statistics. it's an elegant way to factor the sourcecode for a program, I wonder if Raymond Boyce didn't die young what kind of amazing technology we might have today.
> the second programming language everyone needs to know
Do they though? I've been writing SQL for over twenty years, and my experience is that LLMs have been better at writing it than I am for at least most of 2025, for most use cases. I have zero doubt that I will only be writing SQL when I want to for fun no later than sometime 2027.
An LLM can respond to any online discussion about <x> is a good approach for solving a particular class of problems with LLMs can do <x> better than a human better than you.
I’ve been heads-down on publishing a JavaScript full-stack metaframework before the end of the year. However, in the past two weeks I’ve been goaded by Claude Code to extract and publish a separate database client because my vision includes Django-style admin/forms. The idea is to use Zod to define tables, and then use raw SQL fragments with JavaScript template tags. The library adds a tiny bit of magic for the annoying parts of SQL like normalizing join objects, taking care of SELECT clauses and validating writes.
I’m only using it internally right now, but I think this approach is promising. Zod is fantastic for this use-case, and I’m sad I’ve only just discovered it.
I’ve always hated SQL, but fortunately LLMs write it so well that it’s effectively become a read-only language now. You just need to know enough to check the output.
I much prefer Kusto query language. SQL needs a few tweaks so that it's more type safe and supports auto completion. Some engines support From-first which is a good start.
If you do backend web development in 99% of software companies then being very good at whatever your RDBMS is is a superpower.
It's definitely worth learning SQL very well, but you also need to learn the data structures your RDBMS uses, how queries translate into operations on that data, and what those operations look like in a query plan.
You can go surprisingly far with just that knowledge.
I've always gravitated towards query languages and SQL is one of my favourites. I've never really understood the need for ORMs and other abstractions but then I'm not a software developer.
If I was going to chose a "third" language I'd say regex.
You should also be able to reliably generate working code with LLMs, but you can't. They aren't a good tool until they actually work when they are supposed to.
The basic thesis is that the relational model and SQL has been the prevailing choice for database management systems for decades and that won't change soon.
The SQL standard defines more of an aesthetic than an actual language. Every database just extends it arbitrarily and anything beyond rudimentary queries is borderline guaranteed to be incompatible with other databases.
When it comes to procedural logic in particular… you have almost zero chance you’re dropping into that into another database and it working — even for rudimentary usage.
SQL-land is utterly revolting if you have any belief in standards being important. Voting for Oracle (itself initialized as a shallowly copied dialect of IBM SQL, and deviated arbitrarily) as the thing to call “standard” is just offensive.
The advice to learn SQL is because it's everywhere. Now it has inertia, and a better way of doing things has an uphill battle. In 1980-s somebody compared working with SQL to drinking data through a straw, comparing to swimming in data with APL. We had a recent article comparing modern SSD delays and RAM sizes to those which defined architectures of SQL systems of recent decades - we can perhaps reengineer our databases better for modern opportunities. But all these approaches have to deal with SQL as an entrenched technology. Probably a task for a company of a Google class.
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[ 2.8 ms ] story [ 53.1 ms ] threadThe relational model is pretty simple though. Pandas is an awful mess.
Just write SQL. I figured this out when I realized that my application was written in Rust, but really it was a Postgres application. I use PG-specific features extensively. My data, and database, are the core of everything that my application does, or will ever do. Why am I caring about some convenient abstractions to make it easier to work with in Rust, or Python, or whatever?
Nah. Just write the good SQL for your database.
ORMs are one of those things that a lot of people think is a replacement for knowing SQL. Or that ORMs are used as a crutch. That has nothing to do with it. Very similar to how people here talked about TypeScript 10 years ago in a very dismissive way. Not really understanding its purpose. Most people haven't used something like Entity Framework either which is game changing level ORM. Massive productivity boost, and LINQ rivals SQL itself in that you can write very small yet powerful queries equivalent to much more complex and powerful SQL.
I've definitely had issues when using sqlalchemy where some REST API type returns an ORM object that ends up performing many queries to pull in a bunch of unnecessary data. I think this is harder to do accidentally with SeaORM because the Rust type system makes hiding queries and connections harder.
Most of my usage of SeaORM has been as a type query builder, which is really what I want from an ORM. I don't want to have to deal with lining my "?" or "$1" binds or manually manipulate strings to build a query. IMO a good query builder moves the experience closer to writing actual SQL, without a query builder I find myself writing "scripts" to write SQL.
You may not need to use an ORM, but hand writing SQL, especially CRUD, should be a terminable offense. You _cannot_ write it better than a process that generates it.
I understand that's the convention according to the IEEE and Wikipedia [1], but the name itself - Structured Query Language - reveals that its purpose is limited by design. It's a computer language [2] for sure, but why programming?
[1] https://en.wikipedia.org/wiki/List_of_programming_languages
[2] https://en.wikipedia.org/wiki/Computer_language
Do they though? I've been writing SQL for over twenty years, and my experience is that LLMs have been better at writing it than I am for at least most of 2025, for most use cases. I have zero doubt that I will only be writing SQL when I want to for fun no later than sometime 2027.
I’ve been heads-down on publishing a JavaScript full-stack metaframework before the end of the year. However, in the past two weeks I’ve been goaded by Claude Code to extract and publish a separate database client because my vision includes Django-style admin/forms. The idea is to use Zod to define tables, and then use raw SQL fragments with JavaScript template tags. The library adds a tiny bit of magic for the annoying parts of SQL like normalizing join objects, taking care of SELECT clauses and validating writes.
I’m only using it internally right now, but I think this approach is promising. Zod is fantastic for this use-case, and I’m sad I’ve only just discovered it.
https://github.com/bikeshaving/zen
Put it together, it's pure gold!
It's definitely worth learning SQL very well, but you also need to learn the data structures your RDBMS uses, how queries translate into operations on that data, and what those operations look like in a query plan.
You can go surprisingly far with just that knowledge.
A great resource is https://use-the-index-luke.com/
If I was going to chose a "third" language I'd say regex.
The basic thesis is that the relational model and SQL has been the prevailing choice for database management systems for decades and that won't change soon.
Resubmitted because it's a good one: https://news.ycombinator.com/item?id=46359878
https://en.wikipedia.org/wiki/Transact-SQL
SQL/PSM is a general ISO standard that grew out of Oracle PL/SQL, is rooted in ADA, and is implemented by a large range of databases.
https://en.wikipedia.org/wiki/SQL/PSM
Standards are important.
When it comes to procedural logic in particular… you have almost zero chance you’re dropping into that into another database and it working — even for rudimentary usage.
SQL-land is utterly revolting if you have any belief in standards being important. Voting for Oracle (itself initialized as a shallowly copied dialect of IBM SQL, and deviated arbitrarily) as the thing to call “standard” is just offensive.
The advice to learn SQL is because it's everywhere. Now it has inertia, and a better way of doing things has an uphill battle. In 1980-s somebody compared working with SQL to drinking data through a straw, comparing to swimming in data with APL. We had a recent article comparing modern SSD delays and RAM sizes to those which defined architectures of SQL systems of recent decades - we can perhaps reengineer our databases better for modern opportunities. But all these approaches have to deal with SQL as an entrenched technology. Probably a task for a company of a Google class.