Case Study: CERN cut SCADA archive storage 7× with TimescaleDB
Key results
The challenge
CERN's legacy SCADA archiving system (the RDB Archiver, in use since 2008) was tightly coupled to Oracle, carried significant technical debt, and had rigid schemas and performance limits. It managed millions of daily time-series data points across more than 800 systems.
The solution
CERN deployed its NextGen Archiver (NGA) with a TimescaleDB backend, using the PostgreSQL extension's columnar compression, continuous aggregates and pluggable multi-database architecture.
“For the read results using compression, we have observed pretty significant speed-ups, from 10x to 40x, depending on your query, range, and data frequency.”
MZMartin ZemkoSoftware Engineer, CERN
The results, in context
CERN reported a 7× storage reduction (78-95% space savings depending on data type) and query speed-ups of 10-40× on compressed data depending on query, range and data frequency. Write throughput reached 77,000 rows per second against a 20,000 rows/second requirement. The system ran on roughly 500 systems at the time of writing, with full production planned for 2027.