by Angela Guess
Jim Scott recently wrote in Smart Data Collective, “If you’re looking to take advantage of sensors, you will likely have to update your data store to handle the workload. Once you’re set up data-wise, get ready to monitor everything from weather and the environment to overseas factory floors and even fleets of trucks… You might think your data needs for sensors are as tiny as these little devices, but there are several reasons you should consider a NoSQL database. The first reason is that these sensors can send huge amounts of data since they run 24/7. All of that data adds up to the need for a larger storage capacity. While you might be tempted to use an RDBMS, relational databases were never really meant to deal with the kind of data that sensors generate. For one thing, sensor data doesn’t always make sense in tabular format.”
Scott goes on, “SQL was originally designed for relatively static data structured as a table. Data from sensors can change a lot and provides a continuous stream. And you need to be able to add or remove entries on the fly, which can prove difficult with relational databases. NoSQL databases are also more scalable, offering flexibility in data models. You can have a structure similar to SQL with wide tables, or you might choose to go with a document-oriented database, key-value database, or graph database. Time series databases are one of the more obvious choices for Internet of Things applications specifically.”
photo credit: Flickr/ dmje