InfluxDB is the Time Series Database in the TICK Stack

InfluxData’s TICK Stack is built around InfluxDB to handle massive amounts of time-stamped information. This time series database provides support for your metrics analysis needs, from DevOps Monitoring, IoT Sensor data, and Real-Time Analytics. Users can adapt their SQL skills with InfluxQL, so they can get up to speed on this time series database.

Note: Clustering is only available in InfluxEnterprise and InfluxCloud – Compare Editions.


High Performance

InfluxDB is a high-performance data store written specifically for time series data. It allows for high throughput ingest, compression and real-time querying of that same data. InfluxDB is written entirely in Go and it compiles into a single binary with no external dependencies. It provides write and query capabilities with the command line interface, the built-in HTTP API, a set of client libraries (like Go, Java, and Javascript to name a few) and with plugins for common data formats such as Telegraf, Graphite, Collectd, and OpenTSDB.


SQL-Like Queries

InfluxDB provides InfluxQL as a SQL-like query language for interacting with your data. It has been lovingly crafted to feel familiar to those coming from other SQL or SQL-like environments while also providing features specific to storing and analyzing time series data. InfluxQL also supports regular expressions, arithmetic expressions, and time series specific functions to speed up data processing.


Downsampling and Data Retention

InfluxDB can handle millions of data points per second. Working with that much data over a long period of time can create storage concerns. InfluxDB will automatically compact the data to minimize your storage space. In addition, you can easily downsample the data; keeping the high precision raw data for only a limited time, and storing the lower precision, summarized data for much longer or forever. InfluxDB offers two features—Continuous Queries (CQ) and Retention Policies (RP)—that help you automate the process of downsampling data and expiring old data.

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