In this blog post, we talk about the results of Percona’s time series database poll “What Database Engine Are You Using to Store Time Series Data?”
Time series data is some of the most actionable data available when it comes to analyzing trends and making predictions. Simply put, time series data is data that is indexed not just by value, but by time as well – allowing you to view value changes over time as they occur. Obvious uses include the stock market, web traffic, user behavior, etc.
With the increasing number of smart devices in the Internet of Things (IoT), being able to track data over time is more and more important. With time series data, you can measure and make predictions on things like energy consumption, pH values, water consumption, data from environment-aware machines like smart cars, etc. The sensors used in IoT devices and systems generate huge amounts of time-series data.
A couple of months back, we ran a poll on what time series databases were being used by the community. We wanted to quickly report on the results from that poll.
First the results:
[poll id=”16″]
Here are some thoughts:
Thanks for participating in the poll. We’re still running a poll on operating systems, so don’t forget to register your responses. We’ll report on that poll soon, with a new one on the way shortly.
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