New capabilities, including faster query performance and management tooling, advance the InfluxDB 3.0 product line
InfluxDB Clustered general availability gives developers the power of InfluxDB 3.0 for the self-managed stack
InfluxData, creator of the leading time series platform InfluxDB, today announced new capabilities in the InfluxDB 3.0 product suite that simplify time series data management at scale. InfluxData also announced the general availability of InfluxDB Clustered, its self-managed time series database for on-premises or private cloud deployments. The rebuilt InfluxDB 3.0 core delivers high performance, including unlimited cardinality, high-speed ingest, real-time querying, and superior data compression through native object storage to power high-cardinality use cases, including observability, real-time analytics, and IoT/IIoT.
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“We rely on InfluxDB Clustered as the foundation of our customer usage monitoring solution, processing millions of time series data points collected across more than 40 distinct products and services”
“Intelligent, real-time systems require an operational database capable of managing high-speed, high-resolution workloads,” said Evan Kaplan, CEO of InfluxData. “InfluxDB 3.0 is engineered to meet this challenge head-on with industry-leading ingest performance, unlimited data cardinality, and exceptionally low latency querying, giving architects and developers tools to build real-time monitoring and control systems.”
Since its release last year, InfluxData has introduced significant performance improvements to InfluxDB 3.0 for developers to more effectively analyze time series data across systems as data volumes grow. As workloads expand, the need for sophisticated, high-performing systems that support real-time, high-resolution data retrieval and analysis becomes increasingly critical. With new performance improvements in query concurrency, scaling, and latency, InfluxDB 3.0 easily manages large datasets without performance degradation, keeping systems responsive even with high-cardinality data. Combined with existing capabilities such as fast ingestion and leading-edge query performance, developers can now analyze more data at higher speeds without compromising efficiency.
Additional InfluxDB 3.0 capabilities announced today in InfluxDB Cloud Dedicated and InfluxDB Clustered help developers more easily manage large-scale time series workloads:
- New Features in InfluxDB Cloud Dedicated: InfluxDB Cloud Dedicated, InfluxData’s fully managed time series database-as-a-service for enterprise-grade workloads, introduces several powerful enhancements. A new operational dashboard now provides comprehensive visual insights into the performance and health of dedicated clusters, enabling developers to detect unintended workload changes, identify potential bottlenecks, and optimize cluster performance. Single sign-on (SSO) integration allows seamless access to clusters using existing credentials, streamlining the login process. New APIs for management & Token management have been added, allowing customers to automate administrative tasks such as managing users, databases, and tokens within their InfluxDB Cloud Dedicated cluster.
- InfluxDB Clustered Now Generally Available: InfluxDB Clustered, InfluxData’s 3.0 product for on-premises and private cloud environments, is now generally available. Deployed on Kubernetes, it features decoupled, independently scalable ingest and query tiers, providing high availability and exceptional scalability. By separating compute from storage, developers can precisely scale, ingest, and query components independently of their storage requirements. With this GA release, customers gain access to all of the latest performance improvements made in the InfluxDB 3.0 core. They also get the option to utilize InfluxData’s new Helm Chart deployment method for developers using Helm for the deployments.
InfluxDB 3.0 customers run massive time series workloads at a lower cost:
“We rely on InfluxDB Clustered as the foundation of our customer usage monitoring solution, processing millions of time series data points collected across more than 40 distinct products and services,” said Arun Kesavan, Principal Engineer at Verint. “By deploying InfluxDB Clustered on Kubernetes, we gain the flexibility to effortlessly scale our systems in response to growing data workloads during peak usage. This allows us to analyze high-cardinality data in real-time at a significantly reduced cost, providing our team with critical insights faster than ever before.”
“Joby Aviation is pioneering the future of air transportation, where every flight generates massive amounts of time series data from hundreds of sources monitoring thousands of variables,” said Kevin Carosso, Software Engineering Lead at Joby Aviation. “The high performance of InfluxDB Clustered enables us to ingest this data immediately upon landing, compress it efficiently, and meet our data retention requirements while keeping storage costs down.”
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“ju:niz Energy is leading Germany’s decentralized energy transformation, where real-time and historical data drive renewable energy production, storage, and conversion,” said Ricardo Kissinger, Head of IT Infrastructure and IT Security at ju:niz Energy. “Our edge systems generate high-resolution data from tens of thousands of sensors from our batteries and other plant devices, making cloud storage previously cost-prohibitive. With InfluxDB Cloud Dedicated, we’ve eliminated that challenge—ingesting 100 times more data per second and compressing it with remarkable efficiency, allowing us to significantly scale our data storage and analysis while dramatically reducing storage costs.”
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