How do you make decades of time-series data usable at scale? CERN operates 800+ WinCC OA-based SCADA systems that generate hundreds of gigabytes of time-series data every day from Large Hadron Collider experiments to critical infrastructure.

In this on-demand webinar, CERN engineers share how they modernized their legacy archiving stack with the NextGen Archiver (NGA) and TimescaleDB (PostgreSQL) to improve performance, reduce storage costs, and simplify long-term operations.

In this 60-minute session, you’ll learn how CERN:

• Built a pluggable archiving architecture (NGA) to modernize legacy stack

• Reduced storage by up to 95% and sped up historical analytics by up to 40% using TimescaleDB's hybrid rowstore/columnstore architecture

• Supported complex, time-saving metadata by combining relational data and time-series signals in one system

• Designed for maintainability and flexibility, reducing lock-in and technical debt

If you work on industrial monitoring, IoT, observability, or any system that needs fast analytics over large volumes of time-series data, this on-demand session will give you practical patterns you can apply to your own architecture.