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By Cole Bowden
If you’re already running or are familiar with Home Assistant, you’ve likely worked with integrations, maybe a few automations, and possibly MQTT as a way to wire devices together. But webhooks add another layer of flexibility that lets you level up your smart home into a fully-customized, intelligent network. Instead of relying on built-in integrations and being confined to the same local network, you can let external devices and services push events directly into Home Assistant.
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By Charles Mahler
Time series autoregression is a powerful statistical technique that uses past values of a variable to predict its future values. This approach is particularly valuable for forecasting applications where historical patterns can inform future trends. In this hands-on tutorial, you’ll learn how to implement autoregressive (AR) models using Python and see how InfluxDB can enhance your time series analysis workflow.
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By Ben Corbett
Today at Hannover Messe, InfluxData is announcing a strategic partnership with Litmus to address one of the most persistent challenges in industrial data: getting reliable, contextualized telemetry from the shop floor into production systems. Litmus bridges the gap between OT systems and modern IT infrastructure, while InfluxDB serves as the industrial data hub, giving organizations both real-time operational visibility and enterprise-scale historical analysis in a unified architecture.
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By Cole Bowden
In this blog, we’re going to take a look at how you can set up a fully-functioning, robust data pipeline to centralize your data into an InfluxDB instance by collecting and sending messages with the MQTT protocol. We’ll start with a brief overview of the technologies and protocols used in the pipeline, then dive into how you can connect, configure, and test them to ensure your data pipeline is fully functional. It’s going to be a long post, so let’s jump right in.
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By Ben Corbett
If you’ve spent time in industrial environments, you know the problem isn’t a lack of data. It’s collecting it reliably, contextualizing it, and storing it at scale. Most stacks weren’t built to fight all three battles.
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By Daniel Campbell
InfluxDB 3 Explorer 1.7 is a step forward for anyone who wants to manage their time series data without constantly switching between the UI and a terminal. This release adds table-level schema management, the ability to import data from other InfluxDB instances, and a new Transform Data section to reshape your data, all within the Explorer UI.
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By Ryan Nelson
Our Q1 momentum has been focused on a simple goal: making InfluxDB easier to operate, easier to scale, and faster to put to work. Across Telegraf, InfluxDB 3, and our managed offerings, these updates reduce friction in how teams collect, process, and scale time series workloads.
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By Ryan Nelson
The Processing Engine is one of the most powerful features in InfluxDB 3. It lets you run Python code at the database—transforming data on ingest, running scheduled jobs, or serving HTTP requests—without spinning up external services or building middleware. You define the logic, attach it to a trigger, and the database handles the rest. Since launching the Processing Engine, we’ve been building out both the engine itself and the ecosystem of plugins that run on it.
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By Peter Barnett
We’ve spent the last few months listening to how teams are running InfluxDB 3 in the wild. The feedback was clear: as you scale, you need less “guesswork” and more control. Today’s release of InfluxDB 3.9 is our answer to that. As more teams move InfluxDB 3 into production, our focus has shifted toward the operational experience: how you manage the database at scale, how you ensure it remains secure, and how you provide a seamless experience for users.
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By Charles Mahler
MRO stands for maintenance, repair, and operations. It refers to the activities, supplies, and services that keep equipment, facilities, and infrastructure running safely and efficiently. Every industry that relies on physical assets depends on MRO, whether that means replacing a worn bearing on a production line, restocking safety gloves in a warehouse, or servicing an HVAC system in a hospital.
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By InfluxData
Telegraf is InfluxData’s open source agent for collecting metrics, and it’s used everywhere. In this quick overview, Product Manager Scott Anderson shares what makes it stand out, from more than 5 billion downloads to a huge plugin ecosystem with 400+ integrations. It’s also built by a strong community, with over 1,300 contributors and thousands of GitHub stars. That momentum is a big part of why Telegraf keeps growing.
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By InfluxData
InfluxDB 3 on Amazon Timestream for InfluxDB now scales to 15-node clusters, unlocking higher ingestion, greater query concurrency, and real-time performance at scale. In this video, PM Pete Barnett breaks down what this means for high-resolution, high-velocity workloads, and how you can scale from Core to Enterprise with zero downtime or data migration.
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By InfluxData
In this video, Senior Developer Advocate Cole Bowden walks you through the key similarities and differences that exist in InfluxDB 3 Core and InfluxDB 3 Enterprise. As an open source offering, Core thrives at data collection on the edge and providing real-time insights into fresh data, while Enterprise includes support, compaction for performant historical analysis over wide windows, better scaling and security for enterprise-scale operations.
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By InfluxData
In this video, we walk you through setting up and getting started with the InfluxDB Explorer UI - a convenient, easy way to query and explore your data. This walks you through installation and connecting with the Explorer UI, as well as loading data, running queries, and setting up a basic dashboard.
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By InfluxData
In this video, we go over getting started with InfluxDB, including downloading, installing, writing, and reading data with a couple different clients.
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By InfluxData
Explorer is the new UI for InfluxDB 3 Core (open source) and Enterprise. It brings everything into one place: ingesting data, querying, visualizing, and managing your database. It’s designed to remove friction: fewer tools, less context switching, faster feedback.
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By InfluxData
InfluxDB 3 Enterprise uses a cloud-native, diskless architecture to eliminate traditional storage limits. Its stateless design simplifies operations, delivers instant failover with zero data loss, and lets you scale compute and storage independently to petabyte levels without re-architecting your system.
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By InfluxData
Dive into InfluxDB 3 Core, an open source, high-speed recent-data engine. InfluxDB 3 Core is an open source, high-performance real-time data engine (MIT/Apache 2 licensed). It’s built for real-time monitoring, edge data collection and transformation, sensor alerting, and streaming analytics with simplicity and speed.
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By InfluxData
The Distinct Value Cache in InfluxDB 3 speeds up metadata queries and tag value lookups for faster, more responsive UIs. The Distinct Value Cache in InfluxDB 3 delivers sub-30 ms lookups for tag values and series metadata, making exploratory queries and UI dropdowns quick and responsive. By reducing latency on these common operations, it allows developers to build real-time monitoring and analytics tools without extra complexity.
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By InfluxData
InfluxDB 3 Enterprise is engineered for performance and designed for flexibility, delivering high-scale, production-ready time series data management with operational simplicity. InfluxDB 3 Enterprise is built on a cloud-native, diskless architecture that removes the limits of traditional storage. It’s easy to deploy, scales effortlessly, and eliminates the complexity of managing clusters so you can deploy your way and meet the unique demands of your environment.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.