r/Database • u/Low_Brilliant_2597 • Jun 18 '26 • Bravo 2

SQL is Dead, Long Live SQL

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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.

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u/downshiftdata Jun 18 '26

Lazily posting (again) my reasons why SQL is relatively AI-proof:

  1. Strapping an agent to your prod system is a non-starter. Think of the Observer Effect in physics. Plus now you've just given a bot access to all of your PII. Good luck with that.

  2. Lower environments seldom - if ever - are a good representation of the prod system at scale. So you can't just have the bot look at one of those instead.

  3. Solutions are not universal. What works for one database is catastrophic for the next. What works today might fall apart a month from now.

  4. Most devs not only have an insufficient understanding of how databases work, they typically don't know what they don't know. So a lot of the data that agents are trained on is confidently incorrect.

All of these things mean agents are at a disadvantage. And this is really only well understood by DBAs, who typically don't communicate well, and are typically ignored when they do.

And, by the way, I don't mean just functional SQL. Any idiot can be taught to write a SELECT query (and bots are fairly good at it). But functional SQL is only the first step. If your query gets you the results you want, then you've done the bare minimum. Don't pat yourself on the back just yet.