What does managing your time-series data mean?
The essential strategy for reducing costs and improving performance by managing how you store, query, and archive data.
TimescaleDB features for managing time-series data
- Continuous aggregates compute common queries in the background
- User-defined actions let you customize background tasks with your data
- Data retention lets you decide how and when you want to archive data
See how to manage your time-series data
Watch the video and learn how to use several TimescaleDB features to manage the lifecycle of your time-series data.
Save money and improve performance of time-series data
Developers ❤️ TimescaleDB
“TimescaleDB allows us to scale our services without introducing completely new technologies to the mix...This is important so that we can keep the team small and agile and stay focused on features, not infrastructure.”
Pedro Kostelec, CTO, Sentinel Marine Solutions
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“We use archiving functions to copy some data into long-term storage, and a drop_chunks policy to ensure that rows older than one week are dropped to prevent unlimited table growth.”
Caroline Rodewig, Senior Software Engineer and Predict Crew Lead at FlightAware
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Continuous aggregates policies
Achieve greater performance by building and automatically refreshing common queries in the background.
See the how-to guideRead the docs
Data retention
Manage your data by setting data retention and tiering rules.
See the how-to guideRead the docs