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ArangoDB Finalizes 4.2 Million Euro Investment Led by Target Partners

Funding to accelerate and strengthen the company’s US-based presence

ArangoDB, the company behind one of the fastest growing next generation databases, closed the final tranche of a 4.2 million Euro investment led by Munich-based venture capital firm Target Partners.

The company is developing the open-source NoSQL database ArangoDB, which combines three major data models (graph, key/value, JSON-documents) in one database and with one query language. ArangoDB allows startups and enterprises to speed up innovation cycles, simplify technology stacks and increase on-time and on-budget delivery of software projects.

Claudius Weinberger ArangoDBClaudius Weinberger, Co-Founder and CEO, declared: “We’ve found in Target Partners a supportive and knowledgeable investor. After reaching important business milestones and expanding our customer footprint globally, we will use this funding to further accelerate and strengthen our US-based presence.”

ArangoDB is on an upward growth trajectory. The company recently hired key executives from the likes of MongoDB, MariaDB, and Oracle, further enhancing its customer facing functions. Talented engineers joined from Dell/EMC research lab to extend product leadership.

Kurt MuellerKurt Müller, Partner at Target Partners said: “Our investment in ArangoDB has proved to be very successful. After gaining traction on the product side, the company aggressively moved to sign landmark deals with some of the largest global organizations. This motivated us to further invest in the team and the growth.”

ArangoDB has an enthusiastic global community with over 2 million downloads so far and already close to 4,000 github stargazers. Over 3,000 organizations, including Fortune 50 companies, currently use ArangoDB worldwide for various use-cases including e-commerce, Internet of things, analytics, fraud detection, personalization, and genomic research. With its newly released Enterprise Edition, the company enables enterprises to scale deployments, including high-performance graph cases.


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