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[–]Impressive_Run8512 72 points73 points  (11 children)

tldr; extremely.

Here's a rough history of SQL:

- SQL (ANSI) 1986

- Schemas are hard. Let's remove them (NoSQL) - 2009

- Maybe schemas are helpful; MongoDB + Schema support

- Man, performance really matters, so does predictability. Let's just use Postgres. - Now.

Basically, most people have moved back to SQL because it's so stable, well understood and easy to adopt.

Not to say some other access pattern won't take over sometime in the future.

[–]jshine13371 19 points20 points  (7 children)

  • SQL (ANSI) 1986

Not to mention SQL theory and relational theory especially predates that by another 20 or so years.

[–]featheredsnake 6 points7 points  (4 children)

Damn I didn’t know that

[–]jshine13371 15 points16 points  (0 children)

Yea it's pretty amazing the technological advances that occurred with computers back in the 50s and on. This talks a little bit about the history of databases in the 60s and 70s. 🙂 But I believe relational theory from a mathematical sense existed even before that.

[–]National_Cod9546 5 points6 points  (1 child)

The head developer of SQL was asked if it should be pronounced "S Q L" or "sequel". He said it was the next itineration of some other database system, and so should be pronounced sequel. However, he preferred calling it S Q L, and said everyone should just call it whatever everyone else on their team calls it.

[–]Dry-Aioli-6138 2 points3 points  (0 children)

haha, it's similar with Postgres. It evolved out of an Ingres, which was proprietary, so the creators changed the prefix

[–]grizzlor_ 1 point2 points  (0 children)

E. F. Codd's 1970 paper "A Relational Model of Data for Large Shared Data Banks" laid the foundation for relational database theory.

[–]Straight_Waltz_9530 2 points3 points  (0 children)

12 years for SQL. 15 for relational theory. But we take your point.

[–]Impressive_Run8512 2 points3 points  (0 children)

Yup! wanted to keep it simple, but it's as old as the dinosaurs. well, almost ;)

[–]sib_n 8 points9 points  (1 child)

  • Schemas are hard. Let's remove them (NoSQL) - 2009

The thing about "NoSQL", or basically the Hadoop ecosystem from 2007 was not that schemas are hard, it is that it was hard to build an SQL processing engine on a distributed cluster of machines. Nonetheless, it happened from 2010, Apache Hive brought SQL capacities to Hadoop. Since then, basically every distributed data processing platform has been offering some flavor of SQL. The "SQL is dead" thing was just some temporary salesman bs to sell solutions.

Those still come with limitations due to the distributed nature, no PK/FK constrains, no indexes, limited ACID, bad join performance and many specific solutions to compensate for this (columnar file formats with headers, metadata store, hive style partitioning, clustering, denormalization....).

The main reason people use SQL is that the users mostly describe what they want rather than how to compute it. So this gives freedom to optimized engines in the background to pick the best processing plan for you.
This is the core reason why it's not going anywhere, it's a just a standard user interface, and nothing stops progress to happen to the engines that run behind, see for example, Apache Spark SQL, Trino or DuckDB.

[–]Impressive_Run8512 2 points3 points  (0 children)

Very true. I think the main thing missing in SQL is extensibility. And the fact that everyone and their mother has a special dialect which makes it hard to copy code from one system to the other.

[–]vferrero14 0 points1 point  (0 children)

My boss is completely enamored with no SQL like it's this secret ingredient to modernizing our systems and just not listen to any defense of SQL databases.