We prepared for you a short guide on how to optimize the storage of time-series data in MongoDB with Java+Spring examples.
What is time-series data?
Practical use case of time-series
In our short guide, Kamil, our Java developer, investigated a case of a traffic engineering company. This company needs to collect data on an exact number of cars crossing a particular intersection to manage the traffic-lights algorithm. Each vehicle passing through the road intersection is being reported back to the system. Such an event is what we refer to as a data point in time. Multiple cars passing the intersection are what we call a “series” of that data.
Time-series data can be produced at an irregular rate — in our example, it occurs only when a car passes by — or it can be captured at constant time intervals — for instance, device measurements per second.
Optimizing the storage of time-series data
Storing such as information in typical MongoDB documents has obvious flaws and a significant impact on performance and disk usage. Check out our guide on optimizing the storage of time-series data in MongoDB with Java+Spring examples, which takes you less than 3 minutes.
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