Many companies across the world have chosen MongoDB as the data platform for their IoT workloads. MongoDB makes it easy to store a variety of heterogeneous sensor data in a natural, intuitive way and blend it with enterprise data, allowing you to integrate IoT apps across your organization. Experience setting up your own temperature sampling solution in the article: Implementing an end to end IoT solution in MongoDB. Through the article you will learn how to use a TMP36 analog sensor, a NodeMCU microcontroller, a Raspberry Pi, MongoDB Stitch and MongoDB Atlas!
While trivial, this example highlights the building blocks of more complex solutions by walking through the basic concepts of capturing data from a sensor and follows the path of data all the way to a database backend. Once in MongoDB you can use tools like MongoDB Compass to build aggregation pipelines or leverage analytical and machine learning technologies like Apache Spark and statistical languages like R to derive additional insights from your data.
IoT use cases can generate high volume streams of time-series data. Check out our upcoming webinar, "Time Series Data and MongoDB: Best Practices" for insights into optimal MongoDB schema design and analysis for time series data.