InfluxData

San Francisco, CA, USA
2012
  |  By Anais Dotis-Georgiou
The long-awaited InfluxDB 3 Core is finally here, introducing a powerful new way to manage your time series data. InfluxDB 3 Core is an open source recent-data engine for time series and event data. It’s currently in public Alpha under MIT/ Apache 2 license. In this post, we’ll dive into how to query and write data using the Python client library, unlocking the full potential of InfluxDB v3 Core with clear, hands-on examples.
  |  By Paul Dix
New InfluxDB 3 Core and InfluxDB 3 Enterprise products now available for alpha testing. Today we’re excited to announce the alpha release of InfluxDB 3 Core (download), the new open source product in the InfluxDB 3 product line along with InfluxDB 3 Enterprise (download), a commercial version that builds on Core’s foundation. InfluxDB 3 Core is a recent-data engine for time series and event data.
  |  By Evan Kaplan
Today, we are announcing the public alpha of the newest additions to the InfluxDB 3 time series database product line: InfluxDB 3 Core, our latest open source product, and InfluxDB 3 Enterprise, a commercial version built on Core that provides enhanced functionality for enterprise-scale applications.
  |  By Suyash Joshi
When Netflix buffers or AWS goes down, teams spring into action. But how do they identify and fix issues so quickly? The secret lies in intelligent DevOps monitoring, a system that not only watches but understands your infrastructure’s behavior. In this hands-on guide, we’ll build a modern monitoring pipeline that helps you catch and resolve issues before your users notice them. We have prepared a sample Python application that we encourage you to play with to understand the system in action.
  |  By Andrew Lamb
Apache DataFusion has reached an inflection point. It has matured beyond early adopters and is now a viable choice for anyone building highly performant analytic systems. I predict 2025 will bring a significant acceleration in the number of systems built on DataFusion, and my focus this year is to help drive that growth.
  |  By Anais Dotis-Georgiou
InfluxDB is a purpose-built time series database designed to handle high-write throughput and large volumes of time-stamped data. From monitoring system metrics to tracking IoT device readings and analyzing financial trends, it excels in scenarios where time is a fundamental factor. With the release of InfluxDB v3, users now benefit from dual query language support: SQL and InfluxQL.
  |  By Jessica Wachtel
This tech paper was created by IIoT World and InfluxDB. This post was originally published on IIoT World. The Industrial Internet of Things (IIoT) is revolutionizing industries like manufacturing, energy, and logistics by creating more intelligent, interconnected systems that elevate productivity and efficiency. With IIoT, machines, systems, and sensors are linked in real-time, streamlining industrial automation and making predictive maintenance a reality—all while reducing downtime and costs.
  |  By Product
The stakes are high in Aerospace manufacturing and operations. Aerospace systems are highly complex and require extremely precise engineering—every part of an aircraft or spacecraft must work together flawlessly, and error tolerance is minuscule. Ensuring that all components work perfectly under various conditions (pressure, temperature, vibration) is vital. The cost of building and operating aerospace systems is enormous.
  |  By Community
In a world driven by data, efficient time series data management is a growing concern. APIs play a significant role in automating tasks, especially in cloud-based environments. Go, with its high performance and concurrency, is quickly becoming one of the standard languages for writing cloud infrastructure and utilities for managing streams of data.
  |  By Andrew Lamb
This blog was originally published on Apache DataFusion Project News & Blog I am extremely excited to announce that Apache DataFusion 43.0.0 is the fastest engine for querying Apache Parquet files in ClickBench. It is faster than both DuckDB and chDB/Clickhouse using the same hardware. It also marks the first time a Rust based engine holds the top spot, which has previously been held by traditional C/C++ based engines.
  |  By InfluxData
Demo of setting up observability of event and metrics for a python flask web app with real time visulization. Data is stored and queried from InfluxDB 3 Core (alpha) database.
  |  By InfluxData
This is quick tutorial using our three most popular technologies. This will be a basic overview, for more details on each technology in particular please check out our other videos.
  |  By InfluxData
This is short video going over getting started with InfluxDB. Meant to be a simple tutorial to get you started.
  |  By InfluxData
This is short video describing what makes time series data unique. This is a common question we get asked about within our community.
  |  By InfluxData
This is a short video describing retention policies in InfluxDB, this is a concept used in all 3 version of influx.
  |  By InfluxData
Veteran developers and staff engineers at InfluxData, Nga Tran and Andrew Lamb, have an honest conversation about dealing with software bugs. Bugs can be frustrating, but they can also be thrilling. They are a sign that people are actually using your software - and that's a good thing! Andrew and Nga talk through a recent bug their team encountered, how they approached resolving the issue, and what considerations go into building a permanent fix.
  |  By InfluxData
Veteran developers and staff engineers at InfluxData, Nga Tran and Andrew Lamb, discuss what it was like to rewrite InfluxDB for version 3.0. Several factors prevent companies, especially startups, from rewriting their products. But what does the process look like once a company embarks on a rewrite? And how do they balance innovation with user feedback?
  |  By InfluxData
InfluxData staff engineers Nga Tran and Andrew Lamb discuss what separates a coder from a software engineer.
  |  By InfluxData
To the unfamiliar, building with open source tools may seem like the kind of chaos that leads to Boaty McBoatface-like decisions. Andrew Lamb, staff engineer at InfluxData and PMC for the Apache DataFusion project, provides insight from a developer and a PMC perspective about what it's like to build with, and manage a major open source project. InfluxData recently rebuilt its core database using Apache projects: Flight, DataFusion, Arrow, and Parquet, dubbed the FDAP stack.
  |  By InfluxData
Using open source projects from the Apache foundation to build low-level database software drives innovation. Andrew Lamb, Staff Engineer at InfluxData and PMC for the Apache DataFusion project, discusses the components of the FDAP stack - Flight, Arrow, DataFusion, and Parquet, explaining how building with these tools helps companies focus on innovation instead of spending dev cycles reinventing the wheel.
  |  By InfluxData
Everything related to how IT services are delivered and consumed is undergoing tremendous change. Monolithic architectures are being replaced by microservices-driven apps and the cloud- based infrastructure is being tied together and instrumented by DevOps processes.
  |  By InfluxData
Companies are committed to delivering on higher levels of customer satisfaction for their online services. Unfortunately, many organizations trying to support these initiatives take an interrupt-driven approach where they scramble to fix things when they break. However, to manage to these high levels of SLAs, you should take a structured approach in order to reduce the amount of unscheduled downtime by proactively monitoring and managing your systems.
  |  By InfluxData
This paper reviews how an IoT Data platform fits in with any IoT Architecture to manage the data requirements of every IoT implementation. It is based on the learnings from existing IoT practitioners that have adopted an IoT Data platform using InfluxData.
  |  By InfluxData
In this technical paper, we'll compare the performance and features of InfluxDB 1.4.2 vs. Elasticsearch 5.6.3 for common time series workloads, specifically looking at the rates of data ingestion, on-disk data compression, and query performance. This data should prove valuable to developers and architects evaluating the suitability of these technologies for their use case.
  |  By InfluxData
In this technical paper, we'll explore the aspects of scaling clusters of the InfluxEnterprise product, primarily through the lens of write performance of InfluxDB Clusters. This data should prove valuable to developers and architects evaluating the suitability of InfluxEnterprise for their use case, in addition to helping establish some rough guidelines for what those users should expect in terms of write performance in a real-world environment.
  |  By InfluxData
In this technical paper, InfluxData CTO - Paul Dix will walk you through what time series is (and isn't), what makes it different than stream processing, full-text search and other solutions. He'll also work through why time series database engines are the superior choice for the monitoring, metrics, real-time analytics and Internet of Things/sensor data use cases.
  |  By InfluxData
As the number of metrics collected and acted on increases, developers need a solution that is fast and efficient to keep up with the demands of their solutions. We'll compare the performance and features of InfluxDB and OpenTSDB for common time series db workloads, specifically looking at the rates of data ingestion, on-disk data compression, and query performance. This data should prove valuable to developers and architects evaluating the suitability of these technologies for their use case.
  |  By InfluxData
In this this technical paper, we'll compare the performance and features of InfluxDB vs MongoDB for common time series workloads, specifically looking at the rates of data ingestion, on-disk data compression, and query performance. This data should prove valuable to developers and architects evaluating the suitability of these technologies for their use case.
  |  By InfluxData
In this technical paper, we'll compare the performance and features of InfluxDB and Cassandra for common time series workloads, specifically looking at the rates of data ingestion, on-disk data compression, and query performance. This data should prove valuable to developers and architects evaluating the suitability of these technologies for their use case.
  |  By InfluxData
To help provide a better understanding of how to get the best performance out of InfluxDB, this technical paper we will delve into the top five performance tuning tips for improving both write and query performance with InfluxDB. Topics covered include cardinality, batching, down-sampling, schema design and time-stamp precision.

InfluxData, the creators of InfluxDB, delivers a modern Open Source Platform built from the ground up for analyzing metrics and events (time series data) for DevOps and IoT applications. Whether the data comes from humans, sensors, or machines, InfluxData empowers developers to build next-generation monitoring, analytics, and IoT applications faster, easier, and to scale delivering real business value quickly.

InfluxData provides the leading time series platform to instrument, observe, learn and automate any system, application and business process across a variety of use cases:

  • DevOps Observability Observing and automating key customer-facing systems, infrastructure, applications and business processes.
  • IoT Analytics Analyzing and automating sensors and devices in real-time delivering insight and value while it still matters.
  • Real-Time Analytics Leveraging the investment in instrumentation and observability—detecting patterns and creating new business opportunities.

Customers turn to InfluxData to build DevOps Monitoring (Infrastructure Monitoring, Application Monitoring, Cloud Monitoring), IoT Monitoring, and Real-Time Analytics applications faster, easier, and to scale.