ime series data is quickly becoming all the rage in big data circles. The primary use case for large amounts of time series data tends to be visualization of collected metrics. This could be the temperature of our house, CPU usage of a remote server, the oil levels of your car, etc. In a nut shell, time series data is:

• Data over a continuous time interval
• Data contains successive measurements across that interval
• Data uses equal spacing between every two consecutive measurements
• Each time unit within the interval has at most one data point

It might look something like this

[
    {
        time: '2016-01-01 00:00:00', // minute 0
        value: 1
    },{
        time: '2016-01-01 00:01:00', // minute 1
        value: 2
    }
]

The