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By Ryan Nelson
Summary: Q2 was about giving teams more leverage with less overhead. Between April and June 2026, releases across Telegraf, InfluxDB 3, and InfluxDB 3 Explorer focused on reducing manual work and putting more control directly in their hands as they scale. Telegraf Enterprise reached general availability, giving teams a centralized way to manage, monitor, and support tens of thousands of Telegraf agents.
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By Daniel Campbell
InfluxDB 3 Explorer 1.9 makes it easier to work with your existing queries. Whether you’re migrating Flux queries to SQL or you’ve been writing in InfluxQL for years, this release helps bring your existing queries forward instead of starting from scratch. For teams moving to v3 from earlier versions of InfluxDB, query migration is often one of the last major hurdles.
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By Scott Anderson
Telegraf Enterprise is now generally available. It combines Telegraf Controller, a centralized management console for Telegraf, with official support from InfluxData. Open source Telegraf remains unchanged. Telegraf Controller is free to start with built-in limits, while a Telegraf Enterprise license unlocks higher-scale limits, audit logging, LDAP/OIDC integration, and commercial support. Telegraf has become the standard for collecting telemetry across cloud, edge, and physical infrastructure.
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By Allyson Boate
Satellite operations depend on telemetry as the primary interface to systems that teams cannot directly inspect. Once a spacecraft reaches orbit, signals such as battery levels, temperature, signal strength, and fault codes become the foundation for understanding system health and maintaining control. Telemetry streams continuously, so the underlying data system becomes a critical control point that needs to handle a constant, heavy flow of data.
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By Peter Barnett
In our last release, we introduced a beta of performance updates designed for heavier, more complex time series workloads. InfluxDB 3.10 expands that beta to include enterprise features that give teams more control as they scale and manage larger workloads in InfluxDB 3. This release adds end-to-end backup and restore, row-level deletes, bulk import from Parquet, user management, and an RBAC preview to the previous performance beta.
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By Cole Bowden
Getting InfluxDB 3 up and running is a pretty lightweight process with the installation script. Getting time series data into it is the next step, and for exploration, basic testing, or scenarios where you don’t have a stream of time series data ready to write, that can be a point of friction. That hurdle is particularly high when you want to test the rest of the system around the data you’d be writing.
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By Allyson Boate
Satellite mission operators depend on telemetry to understand spacecraft health, ground system performance, and mission status in real-time. Operation signals help teams identify risks, investigate anomalies, and keep operations moving. When a spacecraft enters safe mode or signal strength drops during a contact window, teams need trusted telemetry immediately. But mission data moves quickly across operational systems, and every handoff makes it harder to control.
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By Charles Mahler
Predictive maintenance is one of the most compelling use cases for time series data. Instead of waiting for equipment to fail or servicing it on a fixed calendar regardless of condition, you watch the live sensor data and act when it indicates that a failure is coming. That “watch the data and act” loop is exactly what the InfluxDB 3 Processing Engine was built for.
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By Cole Bowden
For many operational time series workloads, machine learning can’t operate in the historical way, where data is compiled once and models are trained offline. Sensor readings, infrastructure metrics, application telemetry, energy data, industrial measurements, and financial ticks all share a basic property: the next datapoint is more useful when the system can respond to it immediately (or at least close to immediately).
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By Jason Stirnaman
A more reliable agent that learns your schema, queries your data, and investigates alerts - that’s what’s possible with this release of our MCP server v1.3.0.
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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.