InfluxData

San Francisco, CA, USA
2012
  |  By Anais Dotis-Georgiou /
If you’re an InfluxDB v2 user looking to use InfluxDB v3, you might be wondering how you can migrate data. We are still developing migration tooling. In the meantime, you can use the Quix Template to sync data from InfluxDB v2 to InfluxDB v3. Quix is a complete solution for building, deploying, and monitoring real-time applications and streaming data pipelines using Python abstracted over Kafka with DataFrames.
  |  By Jason Myers /
Ensuring the reliability and performance of applications and systems is vital to a healthy infrastructure. With the exponential growth of data, traditional monitoring approaches fall short of providing real-time insights and proactive problem-solving. That’s where InfluxDB comes into play, offering a robust and scalable solution for all your monitoring needs.
  |  By Anais Dotis-Georgiou /
Integrating time series data with the power of vector databases opens up a new frontier for analytics and machine learning applications. Time series data, characterized by its sequential order and timestamps, is pivotal in monitoring and forecasting across various domains, from financial markets to IoT devices. InfluxDB, a leading time series database, excels in handling such data with high efficiency and scalability.
  |  By Charles Mahler /
In the rapidly changing world of technology, effective monitoring is critical for maintaining your infrastructure and ensuring it performs effectively. While traditional monitoring methods are effective, they can fall short as systems scale and become more dynamic and complex. This article aims to bridge the gap by introducing software engineers to the power of machine learning (ML) in infrastructure monitoring, outlining not just the ‘how’ but the ‘why’ of its application.
  |  By Nga Tran /
This post explains how databases optimize queries, which can result in queries running hundreds of times faster. While we focus on one specific query type that is important to InfluxDB 3.0, the optimization process we describe is the same for any database.
  |  By Company /
SAN FRANCISCO – March 14, 2024 – InfluxData, creator of the leading time series platform InfluxDB, today announced a collaboration with Amazon Web Services (AWS) to deliver Amazon Timestream for InfluxDB, a new managed offering for AWS customers to run InfluxDB open source natively within the AWS Management Console.
  |  By Evan Kaplan /
Today, AWS announced Amazon Timestream for InfluxDB, a new managed offering for AWS customers to run single-instance open source InfluxDB natively within the AWS console. This partnership represents a significant multi-year commitment by AWS to combine its global reach and accessibility with our industry-leading time series database, InfluxDB. AWS adding InfluxDB as a preferred time series database reflects the demand from AWS customers for InfluxDB and evidence of the time series market acceleration.
  |  By Jason Myers /
It’s easy to pitch technology buying decisions as black or white, where one camp is the promised land and the other is a dystopian wasteland where companies and profits go to die. But that doesn’t match reality. Instead, organizations need to balance technical trade-offs with their needs. So, while it’s easy to stand atop the “rip and replace” mountain and shout the virtues of your new technology, that’s not something that most organizations are willing to do.
  |  By Charles Mahler /
Users have higher expectations than ever when it comes to performance and reliability in the apps they use every day. A critical part of meeting these expectations is having a robust monitoring system in place. This article focuses on monitoring applications using a microservice architecture—it will go over key concepts, common challenges, and useful tools every engineer should know.
  |  By Sven Rebhan /
In v1.30.0, Telegraf will remove a few long-standing deprecated plugins. These plugins have been deprecated for a number of years, and plugins with better support and configuration options now replace them. This version of Telegraf also removes a number of configuration options. The full list of deprecated plugins includes: Starting from v1.30.0 Telegraf will show an error message and stop running if any of the plugins or options are present in your configuration.
  |  By InfluxData
InfluxData CEO, Evan Kaplan, discusses the company's expanded partnership with AWS. Open source InfluxDB is now available as a managed service on AWS. Discover what this means for InfluxDB and AWS users, and what additional offerings are in the works to help uers improve their Time to Awesome.
  |  By InfluxData
This is a video going over connecting InfluxDB with @Grafana via the InfluxDB datasource.
  |  By InfluxData
It's your data. You should be able to do whatever you want with it. However, vendor lock-in can trap your data in a single solution, making it extremely difficult to switch to something that better meets your needs. When your data goes in, but doesn't come out—that's a data roach motel. Open source technologies, and solutions built with open source tools, enable organizations to take control of their data, giving them the freedom to put it into and take it out of whatever databases or solutions they see fit.
  |  By InfluxData
InfluxData CEO, Evan Kaplan, talks about time series data workloads, how InfluxDB is purpose-built to support those workloads, and why that is so darn important.
  |  By InfluxData
Turn insights into action–in real-time–using your time series data. Now, more than ever, businesses generate massive amounts of time-stamped data. To get value from that data, you need to be able to ingest and query it in real-time. InfluxDB 3.0, built on innovative open source technology (Apache ecosystem), is the solution startups and enterprises use to achieve real-time insights.
  |  By InfluxData
InfluxData CEO, Evan Kaplan, sits down to talk about AI, how AI has become table stakes for modern software, and the role of time series data as a foundational component for building and training AI models.
  |  By InfluxData
InfluxData founder and CTO, Paul Dix, talks with CMO Brian Mullens about using InfluxDB 3.0 to bring real-time analytics to data lake and data warehouse architectures.
  |  By InfluxData
InfluxData Founder and CTO, Paul Dix, sits down to chat about real-time analytics, the role that time series data plays, and how a time series database complements data lakes and data warehouses for large workloads.
  |  By InfluxData
InfluxData CEO, Evan Kaplan, sits down to discuss why we built InfluxDB 3.0, the key problems version 3.0 solves, and the new opportunities and use cases the advanced capabilities of InfluxDB 3.0 present to users.
  |  By InfluxData
Paul Dix, founder and CTO of InfluxData, discusses how we built support for InfluxQL into the new InfluxDB 3.0, what the advantages of InfluxQL are, and how the broader open source ecosystem makes InfluxQL better.
  |  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.