Most experts agree that a traditional database can’t support the rapidly accelerating mess of unstructured and structured data contained within the enterprise. However, where this consensus falls apart, is on the right approach to tackling the “big data” problem.
In the ongoing battle between the NoSQL and SQL databases, Splice Machine is one of the few young companies that has come down firmly on the side of the latter. Today, the San Francisco startup has raised $4 million in first round funding for its SQL database build on top of the open-source Hadoop Distributed File System.
According to its founders, popular NoSQL databases like HBase and Cassandra Hadoop, can handle large volumes of data that do not fit neatly into structured tables, rows and columns, but do not provide support for the full spectrum of business intelligence (BI) products.
If their solution works, it’s every enterprise investor’s dream. Customers will receive all the benefits of NoSQL (flexible schema for unstructured data, scalability), as well as a close integration with their SQL BI tools and favorite data visualization services like Tableau.
“The NoSQL community threw out the baby with the bath water. They got it right with flexible schemas and distributed, auto-sharded architectures, but it was a mistake to discard SQL,” said Monte Zweben, the company’s CEO in a statement.
With experience at both Oracle and Nasa, Zweben may have the right background for a big data founder. He worked at the NASA Ames Research Center as the Deputy Branch Chief of the Artificial Intelligence Branch, where he dedicated his efforts to the Space Shuttle program. He went on to co-founder Blue Martini Software (which experienced a successful IPO in 2000); prior to that, he was a vice president and general manager at PeopleSoft, acquired by Oracle in 2005.
The company’s closest competitor is Drawn to Scale, a Berkeley-based startup with a SQL database for Hadoop. It has just shy of $1 million in venture funding in the bank.
Splice Machine’s first funding round was led by Silicon Valley firm, Mohr Davidow Ventures.
Filed under: Big Data, Business, Enterprise
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This article originally appeared on VentureBeat
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