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“ArangoDB has built a great product, and with its latest round of financing and the addition of seasoned senior leadership, the company has an amazing foundation in place for further fast expansion. “The addition of Shekhar and James to the ArangoDB executive team comes at a great time for the company,” said Curt Gunsenheimer, Managing Partner at Iris Capital and ArangoDB board member. In addition, incoming CMO James Smith brings more than three decades of marketing experience to ArangoDB, having held senior marketing roles at Punchh, GoodData, OneLogin, Sitecore, Avaya, Electronic Arts, and Intel.
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The company recently raised a $27.8 million Series B financing round to accelerate its continued development of advanced analytics and machine learning capabilities, and its employee base has more than doubled over the course of the past year.
Iyer joins ArangoDB as it enters its next phase of growth. “According to Gartner, ‘Graph forms the foundation of modern data and analytics with capabilities to enhance and improve user collaboration, machine learning models and explainable AI.’ ArangoDB is the only graph database that can truly scale to meet this promise.”
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“Having spent the past two plus decades of my career in the big data, database and analytics space, I am thrilled to join the ArangoDB team,” said Shekhar Iyer, ArangoDB CEO. Read More: Retalon Is Now A Microsoft Partner, Integrating Retail Analytics Solutions With Microsoft Dynamics… I look forward to returning to my product roots in my new role as CPO, where I will be able to focus my time and energy refining our product strategy and roadmap, as well as spend more time with our customers.” “His extensive operational background is exactly what we need at this phase in the company’s growth, and I’m confident in his ability to improve and accelerate the market traction we’ve built as the most scalable open source graph database. “I am pleased to welcome Shekhar to the ArangoDB executive team,” said Claudius Weinberger, ArangoDB co-founder and CPO.
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At ArangoDB, he will leverage his international go-to-market experience to help catapult the company into its next phase of growth. The ARANGODB vertice-edge integration with AQL and client drivers made the data modelling on these complex scenarios effortless. Prior to StreamSets, Iyer has held numerous other executive positions at leading data companies, including Chief Revenue Officer at Couchbase, Global Vice President of Big Data and Analytics at SAP, and Senior Vice President and General Manager at Informatica, among others.
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He most recently served as the President of StreamSets, where he was responsible for worldwide customer operations, including sales, marketing, solution engineering, business development partnerships, field enablement, professional services, and customer success.
Iyer is a global technology executive with a wealth of experience in enterprise software.
Disclaimer: This story is auto-aggregated & summarized by a computer program and has not been created by StartupAround.ArangoDB has built a great product, and with its latest round of financing and the addition of seasoned senior leadership, the company has an amazing foundation in place for further fast expansion. The untapped potential of HPC + graph computingįull disclosure: Before I talk about how critical graph computing +HPC is going to be, I should tell you that I’m CEO of a graph computing, AI and analytics company, so I certainly have a vested interest and perspective here.But I’ll also tell you that our company is one of many in this space - DGraph, MemGraph, TigerGraph, Neo4j, Amazon Neptune, and Microsoft’s CosmosDB, for example, all use some form of HPC + graph computing.And there are many other graph companies and open-source graph options, including OrientDB, Titan, ArangoDB, Nebula Graph, and JanusGraph.Using HPC techniques, a knowledge graph can be sharded across the machines of a large cluster and processed in parallel.Cutting-edge explainability methods such as GNNExplainer and Guided Gradient (GGD) methods are very compute-intensive therefore require high-performance graph computing platforms.
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