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InfluxDB enables the storage of time-stamped data and supports high write rates as well as powerful querying capabilities. The database is especially suitable for IoT applications, monitoring, and analytics. It features native support for tags and a simple query language that helps developers gain insights into their time-dependent data.
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InfluxDB is a time-series database for timestamped measurements, events, and states.
InfluxDB emerged from the need to store and query operational and sensor data efficiently over time. Paul Dix founded InfluxData in 2013, and InfluxDB grew into an open-source project for observability and IoT.
A point contains a measurement, timestamp, tags, and fields. Time series are organized by time and keys; queries and retention rules exploit that structure for current and historical analysis.
It places each measurement in time.
Indexed dimensions group and filter series.
Policies control how long data is kept.
InfluxDB fits metrics, sensors, and events. Cardinality, retention, query behavior, and version compatibility need early planning.
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