InfluxDB 3.0 Revolutionizes Unlimited Cardinality, High Performance Time Series Data Analytics

InfluxData, the creator of the leading time series platform InfluxDB, is launching InfluxDB 3.0, to deliver a series of time series capabilities enacted across the company’s product portfolio, including its new product, InfluxDB Cloud Dedicated. Equipped with a newly rebuilt database and storage engine for time series analytics, InfluxDB 3.0 focuses on enhancing scale and performance features while centralizing its capabilities in a single datastore.

InfluxDB 3.0 calls upon the developmental technologies it was built on—both in its previous iteration as open source project InfluxDB IOx and its programming language designed for performance, safety, and memory management, Rust—to drive massive advancements in performance, high-volume ingestion and compression, real-time querying, and unlimited scale, according to the vendor.

Armed with a plethora of technological advances, InfluxDB 3.0 supports the full range of time series data—including metrics, events, and traces—while enabling the application of new use cases that specifically depend on high-cardinality time series data.

“InfluxDB 3.0 removes cardinality limits in the database,” explained Rick Spencer, VP of product at InfluxData. “Cardinality has long been a thorn in the side of the time series database. By rearchitecting InfluxDB 3.0 to support unbounded cardinality, developers can write any kind of event data with infinite cardinality and slice-and-dice data on any dimension without sacrificing performance.”

The platform’s rebuilding, which now exists as a columnar database, imparts the scale and performance abilities of Apache Arrow upon its real-time query response delivery on edge data, enabling faster workloads—delivering 100x faster queries against high cardinality data—at a lower cost. The columnar database design brings a vibrant upstream ecosystem while reducing the amount of disk space required to store the data due to improved compression ratio, as well as accelerating the processing of analytic-type queries.

“We built InfluxDB around the Apache Arrow project due to its performance,” said Spencer. “Apache Arrow is an in-memory specification for our columnar data, which is fast becoming the standard for high-performance computing. In short, being based on Arrow allows developers to use a vast array of standardized tools (think Pandas, Polars, etc.) in any language while getting the best possible performance.” 

InfluxDB 3.0 delivers unlimited cardinality and high throughput with 10x the ingestion performance for continuous ingest, transformation, and analysis of billions of time series data points per second, without limitations, according to the vendor. The platform’s high compression optimizes data storage costs while simultaneously enabling more storage without an impact on performance; additionally, SQL language support offers greater accessibility toward deep time series insights.

“With SQL support, we’re bringing the most popular data programming language to our database for the first time,” said Spencer. “SQL also allows developers to utilize existing tools and knowledge when working with time series data; it enables broad analytics for preventative maintenance or forecasting through integrations with business intelligence and machine learning tools.”

The newly launched InfluxDB 3.0 is currently available within the following InfluxDB cloud products:

  • InfluxDB Cloud Serverless as an elastic, serverless, fully-managed time series Database-as-a-Service in the cloud
  • InfluxDB Cloud Dedicated as a fully managed time series Database-as-a-Service dedicated to a single tenant

Later this year, InfluxDB 3.0 will be available in two upcoming products: InfluxDB 3.0 Clustered, a self-managed time series database cluster delivered as software for on-premises or private cloud deployment; and InfluxDB 3.0 Edge, a self-managed time series database single-node server delivered as software for local or edge deployment.

InfluxData’s announcement also introduces InfluxDB Cloud Dedicated, a cloud product based on the latest iteration of InfluxDB designed to support large-scale time series workloads. As an appealing upgrade to InfluxDB OSS, this solution is compatible with existing workloads, can run more workloads without cardinality concerns, supports InfluxQL and SQL, democratizes access to a wider suite of tools and high-performance computing options, all while enabling a lower TCO.

“What we are doing is developing a single set of features or capabilities but making them available to users and customers in the best way for them to consume based on their needs,” said Spencer. “InfluxDB Cloud Dedicated is a managed-by-us solution for customers with larger workloads and compliance needs that require single tenancy. “

The recent developments made by InfluxData mark a great leap forward from previous iterations of InfluxDB, as well as introduce a variety of new capabilities that greatly increase users’ ability to gain the most from their database and cloud, according to the vendor.

“Overall, the introduction of InfluxDB 3.0 represents the beginning of a new chapter for the InfluxDB platform, giving users the ability to create time series on the fly from raw, high-precision data, meaning it powers expanded use cases across observability, real-time analytics, and IoT/IIoT,” concluded Spencer.

To learn more about InfluxDB 3.0 and subsequent product announcements, please visit