Time Series

When vmselect asks vmstorage for data, there’s actually quite a bit happening behind the scenes. This article breaks down the process of how vmstorage locates and retrieves your metrics, from finding the right TSIDs to sending back the actual data points.

IndexDB acts as vmstorage’s memory - it remembers which numbers (TSIDs) belong to which metrics, making sure your queries get answered fast. This article walks through how this system works, from the way it organizes data to how it keeps track of millions of timeseries.

vmstorage takes data from vminsert through a concurrency limiter, creates TSIDs for each row, and puts them in memory buffers. Every few seconds, it moves data to storage parts on disk. The system merges parts, removes duplicates, and cleans old data. This turns raw metrics into data users can search.

Time series databases are essential tools in any software engineer’s toolbelt. Their development has been shaped by user needs and countless open source contributors, leading to the healthy ecosystem of options we see today. In this article, you’ll see how time series databases came about, and why so many are open source.

We’re happy to announce VictoriaMetrics Cloud, a hosted monitoring platform and managed service for metrics that allows organizations to monitor and store large amounts of time-series data, without having to run the underlying infrastructure.

With more than 20 new releases of VictoriaMetrics published during 2021, a features roundup seemed appropriate. This blog walks you through the key VM features released in 2021.