I watched 4 hours of Databricks Data + AI Summit 2026 so you don't have to.
My first major project as a Senior Data Engineer, was migrating a decade-old time-series database for a semiconductor company to the cloud. The constraint: sub-second latency on customer queries. Equipment monitoring and predictive maintenance don't work with slow data.
We had Delta Lake for storage, but it couldn't guarantee the query performance we needed.
At the time, Databricks serverless warehouse did not exist.
So we built an additional layer on top: Azure Data Explorer (ADX). The data pipeline became: ingest source data, move to Delta Lake, replicate to ADX, serve queries from ADX.
It worked. Customers got their sub-second latency. But we'd introduced yet another system to maintain, another cost line, another place for things to fail. It was the price of solving the problem at that time.
This past month at Data + AI Summit 2026, Databricks announced Reyden.
A new query engine. Millisecond performance. Massive concurrency. Running directly on your lakehouse. No separate system. No copy. If production matches the demo, a lot of horizontal architectures will collapse into one component. One lake. One source of truth.
That's why I'm watching this closely. They looked at a niche problem I lived through and built a real solution.
Here are the 3 things from the summit that actually matter for data engineers:
- Reyden: Millisecond queries on your lakehouse (no more separate real-time database)
- Genie Zero Ops: Automated pipeline repair that tests fixes before you see them
- Genie Ontology: AI that understands your business through a permission-aware knowledge graph
Did you watch the recent event? What do you think is the next big feature of Databricks to look out for.