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DataStax continues strong momentum in its Q2 FY23 with new funding and partnerships

by techsterhub bureau
September 15, 2022
Reading Time: 2 mins read
DataStax continues strong momentum in its Q2 FY23 with new funding and partnerships

DataStax, the real-time data company, announced continued strong momentum in its fiscal Q2, marked by new funding led by Goldman Sachs, the general availability of its Astra Streaming cloud service, and new global partnerships. The company also shared that its marquee serverless cloud database—Astra DB—maintained strong market adoption, with over 300% year-over-year growth in annual recurring revenue (ARR).

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DataStax also maintained nearly 120% net dollar expansion and over 90% gross dollar retention year-over-year, testaments that its pay-as-you-go Astra DB cloud database is well positioned to help businesses build revenue-generating real-time applications in any economic climate.

“We’re proud to offer an open data stack that just works,” said Chet Kapoor, DataStax chairman, and CEO. “Astra DB and Astra Streaming remove barriers like cost, complexity, and cloud lock-in so that any business can build the real-time applications they need to win. We had some important milestones last quarter, and we couldn’t be more excited about our future.”

In its most recent quarter, DataStax inked new and expansion deals with leading enterprises from around the globe, including Albertsons Companies, Inc., Axlehire, Inc., Brightcove, Bud, Cognira, Inc., Device Insight GmbH, Digital River, Dridco SAU, ecosio GmbH, Endowus, Evinsys, Inc, Fortanix, Inc, Greentube GmbH, Liquid Analytics, Migo Money, Inc, Natura Cosmeticos, Open Text Corporation, Panalgo, Printix, RS Components, Slingshot Aerospace, Inc. and Tondo Smart, Ltd.

Bud is a fintech firm that helps enterprises discover the value of transactional data in the cloud through AI. “We are migrating from utilizing the open source Apache Cassandra database, managed by Bud, to DataStax Astra DB for its multi-region, serverless capabilities on Google Cloud Platform as we continue to scale internationally, operating across four continents, and enabling our internal product teams to focus on our own domain – financial data enrichment. Our hyperscaling financial data platform uses Machine Learning to build highly accurate enrichment models, making transactional data valuable and actionable for our clients and consumers through enhancing affordability assessments, hyper personalization, and user experiences that improve consumer engagement and financial wellbeing.” Michael Cullum, Head of Engineering at Bud.

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