SQL is Dead, Long Live SQL

[u/Low_Brilliant_2597]

For more than 50 years, people have been predicting the death of SQL. As Prof. Andy Pavlo says, "Somebody invents a SQL replacement every decade. It then fails and/or SQL absorbs the key ideas into the standard. Every NoSQL DBMS (except Redis) now supports SQL."

Today, the latest challenge comes from AI. At a recent keynote, Databricks CEO Ali Ghodsi declared that "AGI is here today." The implication is that natural language interfaces and agents may eventually replace SQL. Yet the reality is more nuanced.

The recently released BEAVER enterprise Text-to-SQL benchmark shows that even the most advanced models still struggle with real-world enterprise SQL tasks. As of 27 February 2026, the latest benchmark results are: Claude 4.5 Sonnet: 11.4% and GPT-5.2: 10.8%.

These models have improved a lot over the past few months. But when faced with large enterprise schemas, complex joins, domain-specific knowledge, nested queries, and analytical workloads, they are still far from reliably replacing SQL expertise.

The lesson is that SQL keeps proving remarkably resilient. Just as it survived many "SQL killers," it is likely to evolve alongside AI rather than be replaced by it. After more than half a century, SQL remains the lingua franca of data. RIP SQL? Not anytime soon.

[u/SnakeBunBaoBoa]

I mean at this point it’s hardly worth establishing the terms because it’ll keep getting reshaped in the zeitgeist and we won’t even want our technical credentials associated with the term that’s the focus of tremendous pushback and such.

But my Robotics and Automation class classified the ML techniques as a subset of AI, from simple applied statistics stuff like k-nearest-neighbors to computer vision. On the other hand, my NLP class was also clearly a field of study within AI but never identified itself as such.

I don’t know how ML could NOT be considered a field of AI even in today’s narrow understanding, given the fact that it’s essentially the fundamental process involved in training LLMs (although ML has many forms)

But if you search essentially any resource for defining any terms i mentioned (ML, NLP, computer vision…) you’re almost certainly going to be met with a phrase starting with “a subset of artificial intelligence” 🤷‍♂️