DAIS 2026 · Speaker Spotlight
A conversation
with Fabien Contaminard
On bringing complex event processing into plain SQL with MATCH_RECOGNIZE — and why the humans who own it will own the analysis their agents write.
The Session
Location
San Francisco + Virtual
The DAIS 2026 Speaker Spotlight is a series where we hand the mic to the speakers heading to Data + AI Summit and let them answer five short questions — in their own voice, no press-release polish.
Below, Fabien Contaminard on the SQL clause that turns event sequences into one-liners — and what changes when SQL stops being written by humans and starts being written by agents. Lightly edited for length — otherwise, the words are his.
“
Humans who own this clause own the analysis: they direct what their agents write, and audit what comes back.
— Fabien Contaminard
The topic
What is your talk about, and who is it for?
MATCH_RECOGNIZE brings complex event processing into plain SQL for the data analysts, data engineers and AI agents who'll be writing it.
Why this, why now
What's changed in the last 6–12 months that makes this topic urgent right now?
MATCH_RECOGNIZE just shipped in preview on Databricks. SQL is shifting from being written by humans to being written by agents. Both those statements point the same way: the humans in the room need to speak MATCH_RECOGNIZE fluently, because they're about to teach it to their agents.
The personal stake
Why are you the person giving this talk?
I've spent years running this feature on other technologies. The moment that hooked me was when I understood the purpose and the pattern over rows offered by this clause. It's similar to discovering window functions. The session is me trying to give the room that same moment.
What you'll leave with
What will someone be able to do on Monday morning that they couldn't do before?
Monday morning, you'll detect a fraud pattern, follow a user through a funnel, or catch the precursor to a machine failure in plain SQL. You'll write the sequence the way you'd say it out loud:
- Three failures, then a success.
- Cart, abandon, return.
- Warning, warning, critical.
Read it again… and you've got your SQL query! The engine will find every matching row for you.
The bigger picture
How does this fit into where Databricks — and data and AI more broadly — is heading?
Pattern matching is part of SQL:2016 and now native to Databricks. Agents are writing more and more SQL, and event patterns are getting harder to investigate. Humans who own this clause own the analysis: they direct what their agents write, and audit what comes back.
A note from us
Speakers are the heart of DAIS, and helping the world hear your story is one of the best parts of our job.
Part of the DAIS 2026 Speaker Spotlight series — more voices dropping in the weeks ahead. Got a DAIS speaker you'd love to hear from next? Mention them in the comments — we're always listening.