The amount of data generated today boggles the mind — U.S. companies alone produce 2.5 quintillion bytes daily, enough to fill ten thousand Libraries of Congress in a year — and much of it is of the time-series variety (i.e., data points indexed in time order). Given the sheer volume, it’s no wonder that only 12 percent of companies say they’re analyzing the data they have, according to Forrester Research.

That’s one of the reasons Paul Dix — who’s helped to build software for startups, large companies, and organizations like Microsoft, Google, McAfee, Thomson Reuters, and Air Force Space Command — founded Y Combinator- and Bloomberg Beta-backed InfluxData (formerly Errplane) in 2012. The San Francisco startup develops an open source time series platform, InfluxDB, that is optimized to handle metrics and events in DevOps, internet of things (IoT), and real-time analytics domains. And after a banner year that saw revenue double, InfluxDB 2.0 launch in alpha, and Flux — a functional language for both querying and processing data — debut in technical preview, the startup is gearing up for growth.

InfluxData today announced that this month it raised $60 million in series D lead by Norwest Venture Partners and joined by Sorenson Capital and existing investors Sapphire Ventures, Battery Ventures, Mayfield Fund, Trinity Ventures and Harmony Partners. The round brought the company’s total capital raised to $119.9 million, following a $16 million series B funding round in September 2016 and an $8.1 million series A round in December 2014. The former CEO of MongoDB, Max Schireson, has now joined InfluxData’s board of directors.

The influx of capital will be used to “support further investment of product innovation,” Dix said, with an increased focus on the cloud. And it’ll lay the groundwork for an expanded sales and marketing department, along with a renewed focus on specific uses of its technology, including industrial IoT and networking monitoring and industries such as ecommerce, gaming, and financial services.

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“Today’s IoT and DevOps metric workloads are unique and are best served by a time series database for collection and analysis, instead of a traditional database,” Mark Herring, InfluxData’s CMO, said in an earlier statement. “Purpose-built time series databases are more efficient and work well for today’s workloads — other databases require a lot of overhead to get them to handle this data.”

InfluxDB has no external dependencies and provides an SQL-like language with built-in functions for querying data structures comprising measurements, series, and points. InfluxData says that InfluxDB can achieve millions of writes per second, all while clustering to eliminate single points of failure — in practice enabling things like monitoring, alerting, and notification applications supporting DevOps initiatives, real-time analytics apps, and IoT software that supports millions of events per second.

That’s different from traditional SQL databases, which can become overwhelmed with continuous queries.

InfluxDB is open source — more than 180,000 services currently use it — but commercial products in the form of InfluxCloud (a fully managed and hosted service offering) and InfluxEnterprise (software that can run on-premises or on any cloud provider) have been available for the better part of 18 months. InfluxData’s more than 450 paying customers include eBay, Twitter, Cisco, Siemens, IBM, and Pipeline.

News of the funding comes a week after Microsoft’s acquisition of Citus Data, which develops an extension to PostgreSQL that effectively transforms it into a distributed database. InfluxData also competes with startups like New York-based Timescale, which raised $15 million in January.

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