SQL also brings its own baggage. You still have to manage connection pools, you still have to write migration scripts (even if tools make them easier), and scaling a relational database is still harder than scaling a document store.
This movement isn’t about SQL replacing everything overnight; it’s more like the pendulum swinging back to the middle. We are realizing that the friction of SQL—the need to define types and relationships—was a feature, not a bug. It forces you to design your system before you build it.
SQL and the Lindy Effect
The Lindy Effect is a concept that say the longer a technology survives, the longer it will probably continue surviving. SQL has survived mainframes, the PC revolution, the web, mobile, and it’s now into the AI era. It didn’t survive by being stubborn but by being adaptable. So far, SQL has absorbed JSON, resized itself for web browsers, and integrated with modern languages. But SQL’s revenge isn’t based on destroying the alternatives. It’s more about staying focused on what is essential, proving that sometimes the boring way is really just foundational.
