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One of the biggest quirks that I had bumped up against with TimescaleDB is that it's backed by a relational database. We are a company that ingests around 90M
by a10c 6y ago
One of the biggest quirks that I had bumped up against with TimescaleDB is that it's backed by a relational database.
We are a company that ingests around 90M datapoints per minute across an engineering org of around 4,000 developers. How do we scale a timeseries solution that requires an upfront schema to be defined? What if a developer wants to add a new dimension to their metrics, would that require us to perform an online table migration? Does using JSONB as a field type allow for all the desirable properties that a first-class column would?
- valyala 6y ago90M datapoints per minute means 90M/60=1.5M datapoints per second. Such amounts of data may be easily handled by specialized time series databases even in a single-node setup [1]. > What if a developer wants to add a new dimension to their metrics, would that require us to perform an online table migration? Specialized time series databases usually don't need defining any schema upfront - just ingest metrics with new dimensions (labels) whenever you wish. I'm unsure whether this works with TimescaleDB. [1] https://victoriametrics.github.io/CaseStudies.html https://victoriametrics.github.io/CaseStudies.html