Time series database startup InfluxData Inc. said today it has secured $81 million in funding.

The money comes from a $51 million Series E funding round led by new investors Princeville Capital and Citi Ventures, with participation from existing backers Battery Ventures, Mayfield Fund, Sapphire Ventures and others, plus a $30 million debt facility secured with Silicon Valley Bank. InfluxData said the round brings its total equity funding raised to date to $171 million.

InfluxData is the company behind InfluxDB, an open-source time-series database designed to handle information that’s processed chronologically. As it explains, time can be a critical context that helps to understand data, so those analyzing it can anticipate and determine trends over time.

For instance, heat readings from an industrial temperature sensor must be arranged in the exact order they’re created, with a precise timestamp, so users can track how the heat in a machine fluctuates over long periods. That kind of context is also necessary for various other applications, such as performance monitoring.

InfluxDB provides the foundation for storing and analyzing such data. Notably, the database is simple to deploy and provides high performance, with the ability to perform millions of data operations per second, the company claims. Last year, InfluxData massively expanded the number of data sources InfluxDB is able to support with the addition of edge data replication functionality that allows chronological information to be collected from distributed assets such as sensors.

The company believes InfluxDB is set to become more relevant in a world that’s slowly but surely becoming more instrumented, with a growing number of applications, sensors and systems all emitting relentless streams of time series data that can provide extremely valuable insights when it’s analyzed. Already, the time series database market has matured rapidly in the last two years, InfluxData says, with more companies ranging from startups to Fortune 500 enterprises adopting purpose-built time-series databases.

InfluxDB has apparently become one of the most popular of these data platforms, with InfluxData counting over 1,900 commercial customers, including the likes of Tesla Inc., Hulu LLC, PTC Inc., Siemens AG, Cisco Systems Inc. and IBM Corp. All told, there are more than 750,000 active open instances of InfluxDB up and running globally. InfluxData’s cloud offering, InfluxDB Cloud, is said to represent almost half of the company’s revenue.

“As the pioneer of the modern time series market, we played a pivotal role in driving the recent acceleration in this sector, pushing time series from the edge to the cloud and now, into analytics,” said InfluxData Chief Executive Evan Kaplan (pictured, left, with founder and Chief Technology Officer Paul Dix). “Our investors believe in our vision for time series to power the most sophisticated and large-scale analytics use cases our customers and community can imagine.”

InfluxData said the funds raised today will help to further the development of a new database engine the company has developed, based on the open-source InfluxDB IOx project. It’s said to reimagine InfluxDB as a real-time, columnar datastore that’s able to ingest billions of data points in real time, helping to support additional kinds of time series workloads. According to the company, its new database engine will raise the bar for time series analytics by enabling new use cases that rely on metrics, events, traces and similar kinds of data.

Dharmesh Thakker, general partner at Battery Ventures, said he believes InfluxData’s impressive execution on InfluxDB IOx will pave the way for a new era of real-time analytics.

InfluxData’s experts are regular guests on theCUBE, SiliconANGLE Media’s mobile livestreaming studio. In their most recent appearance, InfluxData’s Brian Gilmore, director of IoT and emerging technology, Lead Developer Advocate Anais Dotis-Georgiou and Director of Engineering Tim Yocum discussed how time-series data is evolving and how the company is improving InfluxDB to cater to those changes:

Image: InfluxData