Visualizations with InfluxDB 3: More Options Than Ever Before
We’ve been working on a number of items here at InfluxData to give you even more options for creating visualizations and dashboards for your time series data in InfluxDB 3.
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Inside the InfluxDB 3 Plugin Ecosystem
Companies today face growing pressure to manage and analyze massive flows of time series data, from IoT sensors to cloud-native infrastructure. Storing this information is relatively straightforward. The greater obstacle is keeping it useful and consistent while balancing a wide range of tools and modern technology platforms that continue to evolve.
Explore the New InfluxDB 3 UI
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.
What's New in InfluxDB 3.5: Explorer Dashboards, Cache Querying, and Expanded Control
InfluxDB 3.5 is now available for both Core and Enterprise, along with updates to the new Explorer UI that make it easier to save, organize, and query your data. This release highlights the biggest updates since our 3.4 release, including Explorer Dashboards in beta, new cache querying capabilities, and stronger operational tools for managing clusters. InfluxDB 3 Core is free and open source, optimized for recent data, and licensed under MIT and Apache 2.
Inside InfluxDB 3's Diskless Architecture
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.
How Nexus BMS Uses Time Series and AI to Power Smarter Buildings
Monitoring equipment isn’t enough for today’s smart buildings; true value comes from being able to predict issues, optimize performance, and take action automatically. Traditional building management systems often fall short, limited to dashboards and alarms that only notify you of an issue after the fact. With the rise of open source hardware, modern databases, and AI-driven diagnostics, facilities can now move from reactive to proactive management.
InfluxDB 3 Core: Open Source, Recent-Data Engine
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.
Distinct Value Cache in InfluxDB 3
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.
InfluxDB 3 Enterprise: Deploy Your Way, Scale on Demand
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.
Building Real-Time Data Pipelines with Kafka, Telegraf, and InfluxDB 3
When milliseconds matter and data never stops flowing, you need a pipeline that can handle high-velocity streaming data with reliability and scale. The modern streaming stack of Kafka, Telegraf, and InfluxDB 3 Core delivers exactly that. To give you a concrete example, this blog works with a fictitious use case: “Papa Giuseppe’s Pizzeria.” Every oven, prep station, and order in this pizza restaurant generates data. Our workflow looks like this.