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Time for funding: Crate.io logs $10M for time series database for industrial IoT applications

Categories Edge Computing News  |  Edge Startups  |  Funding
Time for funding: Crate.io logs $10M for time series database for industrial IoT applications

Crate.io has announced $10 million in additional funding. Existing Crate.io investors including Draper Esprit, VITO Ventures, and Flatz & Partners AG participated together with selected individual investors. The company reports it has now raised approximately $31 million in total funding.

“This new round of funding enables us to accelerate our commercialization efforts,” said Eva Schönleitner, CEO of Crate.io. “We will focus on expanding across several verticals where Crate.io database technologies are key enablers of digital transformation. In addition, we will be broadening our developer and partner community ecosystem. Industry 4.0 initiatives require a ‘team effort.’ Combining forces with leading technology providers and implementors will be essential in order to enable customers to realize the expected operational and technological benefits. The engagement across our ecosystem is key to long-term success and we are building a solid foundation this year.”

Crate.io offers CrateDB as a fully open source time series SQL database, built to scale quickly and capable of ingesting and querying millions of data points every second to deliver actionable insights to organizations in real time. For customers requiring hands-on CrateDB management and optimization, Crate.io provides CrateDB Cloud as a fully managed CrateDB-as-a-service solution. Crate.io also recently launched CrateDB Edge, which now brings the power of CrateDB Cloud to customers’ remote and offline locations.

“The growing importance of machine data analytics and AI demand specifically built data technologies,” says Christian Lutz, co-founder and President, Crate.io. “A distributed SQL architecture that scales horizontally in any cloud and edge enables customers and developers to capture and process the volume of machine data in real-time and at scale, accelerating their success in implementing digital transformation projects.”

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