Time-series specialist InfluxData raises $81M to focus on real-time analytics

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Time-series database provider InfluxData today announced it has raised $81 million in a combination of debt and equity funding. The company said it plans to use the capital to further its recently launched InfluxDB IOx database engine.

The new engine represents a major rewrite of InfluxData’s underlying technology, and it targets the important area of operational analytics. The area is one where systems are connected to highly instrumented data-intensive device populations that now must run at cloud scale, and handle input in real time.

The company turned to the increasingly popular Rust programming language as it created InfluxDB IOx, Evan Kaplan, CEO, InfluxData, told VentureBeat. 

“InfluxDB IOx was developed with Rust, which is designed for speed, efficiency and reliability, and gives users a new high-performance time-series engine to ingest, store and analyze high-volume and high-velocity data in real time, and to derive metrics on the fly from high granularity events,” Kaplan said. 


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The engine, as he explained, powers InfluxDB, reimagining the database as a columnar real-time analytics platform that can ingest billions of data points in real time and deliver query results in a matter of milliseconds.

It offers support for the full range of time-series data and expands the number and variety of use cases that InfluxDB can handle, including observability and distributed tracing, which rely on high-cardinality data.

Funding to accelerate engine rollout

With the fresh funding, which includes $51 million in series E led by Princeville Capital and Citi Ventures and $30 million in debt funding, InfluxData plans to develop the new engine further and accelerate its ongoing rollout and expansion efforts.

Kaplan said InfluxDB plans to introduce new capabilities in bulk data ingest, bulk data export and seamless integration with business intelligence tools such as Tableau and PowerBI, among other improvements. Also planned is a launch of dedicated cloud tiers and a new on-premises product for enterprises based on InfluxDB IOx.

At a time when some large tech companies are scaling back staff, Kaplan said InfluxDB plans to scale its R&D, sales and marketing teams, growing its employee base by about 10% by the end of 2023.

The effort to double down on the real-time engine comes as the number of devices and sensors within an enterprise continues to explode. These devices generate time-stamped data every subsecond, and enterprises need to analyze and contextualize it on a very granular level. InfluxDB IOx seeks to fill this gap, even in scientific, engineering and IoT use cases.

Growing competition for time-series data

Since its founding in 2012 by Paul Dix, now CTO, InfluxData has evolved to become a leading specialist in time-series data, providing enterprises with a purpose-built platform, dubbed InfluxDB, to analyze time-stamped information and produce business-critical trends or predictions. The platform claims a customer base of nearly 2,000.

While the market is often described as a “niche,” the list of time-series database makers has grown a lot since InfluxData’s inception. It includes Imply, Timescale, Druid, Amazon Timestream, Microsoft Azure Data Explorer, QuestDB and Prometheus.

Notably, data cloud leader Snowflake recently time-series forecasting by announcing the intent to acquire Myst.

For its part, InfluxDB head Kaplan says that the company differentiates from other players by supporting high-volume ingestion of all types of time-series data and delivering subsecond responses to queries.

“InfluxData is also one of the very few vendors that offer edge and open-source versions of the product, as well as dedicated instances,” said Kaplan. Nevertheless, he added, he welcomes the fact that numerous emerging open-source vendors are entering the space. Such vendor interest points to growth potential.

(2/8/23 at 4:40p ET: Story corrected to reflect name of InfluxData’s CEO as Evan Kaplan.)

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