Time series data is a sequence of data points generated through repeated measurements indexed over time. The data points originate from the same source and track changes at different points in time. Times series data includes data like stock exchange data, monthly inflation data, quarterly gross domestic product (GDP) data, and logs from IoT sensors.

A look at what Parquet is, how it works and some of the companies using its optimization techniques as a critical component in their architecture. As the amount of data being generated and stored for analysis grows at an increasing rate, developers are looking to optimize performance and reduce costs at every angle possible. At the petabyte scale, even marginal gains and optimizations can save companies millions of dollars in hardware costs when it comes to storing and processing their data.

Devices, developers, applications, and services produce and utilize enormous amounts of JSON data every day. A portion of this data consists of time-stamped events or metrics that are a perfect match for storing and analyzing in InfluxDB. To help developers build the applications of the future, InfluxDB provides several ways to get JSON data into InfluxDB easily.