Materialize, a New York City-based streaming SQL database startup company built on top of the open-source Timely Dataflow project.
Materialize was funded by a $32 million Series B investment led by Kleiner Perkins. Follows an $8 million Series A last year led by Lightspeed Venture Partners, bringing the total funding to $40 million.
The company plans to use the investment to grow its engineering team, prepare the business for growth, and extend product rollout.
These firms see a reliable founding team that includes CEO Arjun Narayan, formerly of Cockroach Labs, and chief scientist Frank McSherry, who created the Timely Dataflow project on which the company based.
At Materialize, they consider it will soon be essential for all information to be always up-to-date at every business. Whether it’s delivering personalized experiences, accurately identifying fraud, building predictive AI, or discovering new business opportunities. The ability to run complex queries on multiple streams of data and keep their answers up to date is critical to making better decisions about the changing world.
Materialize is the first standard SQL interface for streaming data available to engineers looking to build complex queries and multi-way joins without specialized skills or microservices. Unlike other streaming data platforms that claim to be real-time, Materialize computes and incrementally maintains data as generated, so query results are accessible the moment it needs them. This approach provides businesses with correct answers in milliseconds – without interference from late-arriving data.
Bucky Moore, the partner at Kleiner Perkins leading the B round, sees this standard querying ability as a vital part of the technology. He said, Materialize unique ability to provide SQL over streaming data solves the problem, laying the foundation for them to build the industry’s next great data platform.
With this new funding series, they equipped to deliver on an ambitious roadmap, including a fully managed cloud service with tiered storage and replication. Narayan is also excited to broaden the SQL suite. They support and invest in a SQL optimizer, performance and benchmarking work, and making Materialize more flexible and battle-tested.
By: K. Tagura
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