InfluxData

San Francisco, CA, USA
2012
  |  By Jason Myers /
There’s so much talk about AI these days that it seems we quickly forget that AI isn’t a single type of technology. It’s a category, almost an umbrella term for a wide range of different technologies, applications, and approaches. The terms “Generative AI” and “Machine Learning AI” (often referred to as “Real-World AI”) describe two different branches that fall under the broader AI heading.
  |  By Jason Myers /
The Industrial Internet of Things (IIoT) has revolutionized the way industries operate, enabling businesses to collect and analyze data from their operations in real-time. However, managing and analyzing data from diverse sources can be a challenge. While sensors and systems may use the same transport protocols, the shape and type of data generated can vary from one device to another. A lack of uniform, clean data creates challenges and obstacles when it comes to getting timely insights.
  |  By Jessica Wachtel /
To win the space race, aerospace and aviation companies must be fast. The end-to-end cycle of testing, visualizing test data, and making improvements demands swiftness, especially when a single launch yields billions of data points. It starts with real-time access to data. Real-time data analysis with nanosecond precision is crucial for monitoring environmental and habitat conditions when lives are at stake. Speeding up the iteration pipeline is essential but not sufficient. Cost efficiency matters too.
  |  By Jason Myers /
Wrapping up another quarter provides an ideal time to look back on the features we rolled out across various products. Software is never finished, and our engineers have been working hard to deliver improvements to InfluxDB 3.0. This roundup highlights some of the developments and releases over the last few months.
  |  By Jason Myers /
We’ve made the case many times that instrumentation is critical for understanding changes in the physical and virtual worlds. During this recent webinar, panelists discussed the challenges and opportunities of integrating IoT sensors into existing infrastructure, ensuring data quality and accuracy, and leveraging sensor data for operational efficiency and productivity.
  |  By Charles Mahler /
In the modern software development landscape, Continuous Integration and Continuous Deployment (CI/CD) pipelines have become essential. They automate the process of integrating code changes, running tests, and deploying applications. The efficiency and reliability of these pipelines are critical to the overall success of a software project, and CI/CD pipeline monitoring plays a vital role in maintaining and improving these attributes.
  |  By Jason Myers /
Maintenance and repairs for aerospace operations in orbit present a considerable challenge. It’s not easy to dispatch a technician to fix components on a satellite. That’s why it becomes increasingly critical to plan for as many scenarios as possible before launching and deploying these kinds of devices. To understand what’s happening with orbiting devices, companies need data.
  |  By Scott Anderson /
InfluxDB Cloud Dedicated provides fully-managed InfluxDB v3 clusters that power enterprise-grade workloads on a scalable infrastructure dedicated to your workload and your workload alone. As a fully-managed service, InfluxData takes the infrastructure hassle off your plate by monitoring and scaling your cluster when necessary. Until recently, cluster health-related metrics were only available to internal InfluxData support staff.
  |  By Jessica Wachtel /
Prometheus is the go-to observability tool for countless developers and organizations, and for good reason. The popular open source tool doesn’t require any up-front costs or result in vendor lock-in. Prometheus’ short on-ramp makes the technology well-suited for organizations looking to jump-start their cloud monitoring journey.
  |  By Anais Dotis-Georgiou /
In this tutorial, we’ll learn how to build dashboards using Apache Superset and data from InfluxDB Cloud 3.0. This guide will provide practical steps and insights to integrate these powerful tools, helping you visualize your time series data with ease and precision. Whether you are monitoring IoT devices, applications, or infrastructure, you’ll find valuable tips on leveraging Superset and InfluxDB Cloud to enhance your data analytics capabilities.
  |  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
This video will go over how to build a dashboard with different graph types in @Grafana using InfluxDB V3.
  |  By InfluxData
This video goes over how to take advantage of variables in @Grafana while using InfluxDB as a data source.
  |  By InfluxData
This video goes into setting up alerting in @Grafana with InfluxDB as the data source.
  |  By InfluxData
Watch this recent TechCrunch session where two time series data industry leaders–InfluxData Founder and CTO, Paul Dix, and AWS General Manager for Amazon Timestream and Amazon Neptune, Brad Bebee–join moderator Andrew Lamb, Staff Engineer at InfluxData, to discuss.
  |  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
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.