InfluxDB 1.x

InfluxDB is a time series database designed to handle high write and query loads.

What is InfluxDB 1.x?

InfluxDB is the open source time series database that is part of the TICK (Telegraf, InfluxDB, Chronograf, Kapacitor) stack.

Why use InfluxDB 1.x?

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    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. InfluxDB is written entirely in Go and compiles into a single binary with no external dependencies. It provides write and query capabilities with a command-line interface, a built-in HTTP API, a set of client libraries (e.g., Go, Java, and JavaScript) and plugins for common data formats such as Telegraf, Graphite, Collectd and OpenTSDB.

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    SQL-like queries

    InfluxDB works with InfluxQL, a SQL-like query language for interacting with 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 supports regular expressions, arithmetic expressions, and time series-specific functions to speed up data processing.

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    Downsampling and data retention

    InfluxDB can handle millions of data points per second. Working with that much data over a long period can lead to storage concerns. InfluxDB automatically compacts data to minimize your storage space. In addition, you can easily downsample the data; keeping high-precision raw data for a limited time and storing the lower-precision, summarized data for much longer or until the end of time. InfluxDB has two features that help to automate the downsampling and data expiration processes — Continuous Queries and Retention Policies.

The TICK Stack

Collectively, Telegraf, InfluxDB, Chronograf and Kapacitor are known as the TICK Stack.

The TICK Stack is a loosely coupled yet tightly integrated set of open source projects designed to handle massive amounts of time-stamped information to support your metrics analysis needs.

Components of the TICK Stack


Telegraf is a plugin-driven server agent for collecting and reporting metrics. Telegraf plugins source a variety of metrics directly from the systems it runs on, pulling metrics from third-party APIs or even to listen for metrics via a StatsD and Kafka consumer service. It also has output plugins to send metrics to a variety of other datastores, services, and message queues, including InfluxDB, Graphite, OpenTSDB, Datadog, Librato, Kafka, MQTT, NSQ and many others.

Learn more | Documentation | Getting Started


InfluxDB is a time series database built from the ground up to handle high write and query loads. InfluxDB is a custom high-performance datastore written specifically for time-stamped data, and especially helpful for use cases such as DevOps monitoringIoT monitoring, and real-time analytics. Conserve space on your machine by configuring InfluxDB to keep data for a defined period of time, and to automatically expire and delete unwanted data from the system. InfluxDB also offers a SQL-like query language for interacting with data.

Download | Documentation | Getting Started


Chronograf is the administrative user interface and visualization engine of the stack. It makes it easy to setup and maintain the monitoring and alerting for your infrastructure. It’s simple to use and includes templates and libraries that allow you to rapidly build dashboards with real-time visualizations of your data and to easily create alerting and automation rules.

Learn more | Documentation | Getting Started


Kapacitor is a native data processing engine. It can process both stream and batch data from InfluxDB. Kapacitor lets you plug in your own custom logic or user-defined functions to process alerts with dynamic thresholds, match metrics for patterns, compute statistical anomalies, and perform specific actions based on these alerts, like dynamic load rebalancing. Kapacitor integrates with HipChat, OpsGenie, Alerta, Sensu, PagerDuty, Slack and more.

Learn more | Documentation | Getting Started

Companies using InfluxDB 1.x

InfluxDB news
Introduction to Time Series Forecasting with Tensorflow and InfluxDB
Wouldn’t it be nice to be able to perfectly predict the future? We are a long way from being able to do that, but that is basically the goal of anybody working in the data science field — take a bunch of historical data and then try to make future ...
Getting Started with Go and InfluxDB
This article was written by Alexandre Couëdelo and was originally published by The New Stack. Scroll down for the author's picture and bio.  Conventional databases such as PostgreSQL or MongoDB are great at safekeeping the state of your system in a tabular or document format, but what about time-dependent data: ...


Introduction to InfluxDB

This training will show you how to setup Telegraf to pull metrics into InfluxDB and will give a brief overview of how to use InfluxQL to query the data. After this training, you should be well on your way to using InfluxDB.

Available as InfluxDB open source, InfluxDB Cloud & InfluxDB Enterprise

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