The Rise of Open Source Time Series Databases
Time series databases allow you to store and query metrics efficiently. For example, if you want to forecast load on your servers, or identify intermittent faults with your production services, time series databases can help. Besides infrastructure monitoring, time series databases have been invaluable in finance, IoT applications, manufacturing, and more.
Many time series databases, including VictoriaMetrics, are open source. In this article, you’ll see how time series databases came about, and why so many are open source. We’ll also share our insider take on the future of this space.
When people think of databases, they think of relational databases like PostgreSQL and Oracle. Relational databases store data in a table format, where each row contains an instance of the data being described, with each column describing a different aspect of the data. For example, you may have an employees table with name, role, and salary columns. Each row would represent a different employee:
This model works great for many types of data. As long as the amount of data doesn’t get too large, it supports fast querying for specific information and easy updates if the value of a cell changes. However, when data size reaches billions or trillions of rows (typical sizes for time series data), performance degrades.
