Description
Watch how Lakehouse//RT and Zerobus help airline operations teams act on live event data while seats are still open and connections can still be made. When lightning closes a ramp, delays ripple across flights, bags, and connections. This demo simulates a ramp closure at fictional carrier Lakehouse Air, where a network control app flags affected flights, at-risk connections, rebooking options, and hotel needs.
Zerobus streams flight, baggage, and boarding events directly into Unity Catalog tables, with no messaging bus. Lakehouse//RT runs live joins on those tables for dashboards and historical analysis, handling 1,000 concurrent users (about 200 queries per second) plus an 8,000-query burst. Lakehouse//RT is in Beta; ask your account team to enable it.
🎯 What you’ll learn
Deliver sub-second queries at high concurrency for live operational applications
Stream real-time telemetry events directly into Unity Catalog tables using Zerobus
Execute sub-second, multi-table joins on live event data during an operational hold
Track at-risk bags, ripple effects, and rebooking needs
Support concurrent users and query bursts across operations
Serve live and historical analytics from one copy of data
⏱️ CHAPTERS:
00:00 - Introduction and demo overview
01:30: Network control view
02:51: Simulating lightening impact creating ramp closure and operations impact
05:46: Station master, baggage and customer recovery dashboards
09:32: High concurrency & burst load performance test
12:04: Key takeaways and summary
📖 Resources:
Real-time energy trading and analytics on Databricks: https://www.databricks.com/blog/real-time-energy-trading-and-analytics-databricks
🤝 Stay connected:
Website: https://databricks.com
Twitter: https://x.com/databricks/
LinkedIn: https://www.linkedin.com/company/databricks/home/
Facebook: https://www.facebook.com/databricksinc/