Sensor Data Storage Performance: SQL or NoSQL, Physical or Virtual

Sensors are used to monitor certain aspects of the physical or virtual world and databases are typically used to store the data that these sensors provide. The use of sensors is increasing, which leads to an increasing demand on sensor data storage platforms. Some sensor monitoring applications need to automatically add new databases as the size of the sensor network increases. Cloud computing and virtualization are key technologies to enable these applications. A key issue therefore becomes the performance of virtualized databases and how this relates to physical ones. Traditional SQL databases have been used for a long time and have proven to be reliable tools for all kinds of applications. NoSQL databases have gained momentum in the last couple of years however, because of growing scalability and availability requirements. This paper compares three databases on their relative performance with regards to sensor data storage: one open source SQL database(PostgreSQL) and two open source NoSQL databases (Cassandra and MongoDB). A comparison is also made between running these databases on a physical server and running them on a virtual machine. A minimal sensor data structure is used and tested using four operations: a single write, a single read, multiple writes in one statement and multiple reads in one statement.