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SQL-on-Hadoop startup Splice Machine closes $15M in venture capital

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Splice Machine, a startup promising a SQL-on-Hadoop database that can handle both transactional and analytic workloads, has closed a $15 million series B round of venture capital from InterWest Partners, along with Mohr Davidow Ventures. Supporting transactional workloads would put Splice Machine in a good position among the glut of companies and projects letting users perform SQL operations on Hadoop, because most are strictly for analytics. The big question for Splice Machine, though, might be whether companies actually want to run transactions on that data or whether they’re willing to stick to a tried-and-true database for that.

3 Responses to “SQL-on-Hadoop startup Splice Machine closes $15M in venture capital”

  1. Its important to move from traditional systems like RDBMS to NoSQL. Big companies, including Amazon, Google, Facebook and Yahoo, first adopted NoSQL for in-house solutions due to the lack of RDBMS feature support for their ever-changing needs.
    wish you best Splice Machine.

  2. Derrick, you have hit the right point — whether organizations would really be interested in running transactions on Hadoop database. All the use cases we have been seeing address the analytics side and, for lack of fine-grained access control and other related issues, organizations don’t seem to be interested in exploring the transactional side of the coin. Having said this, it’s a differentiator nonetheless.

    • Monte Zweben

      While working with customers, we’ve seen a couple of use cases for transactions on Hadoop (full disclosure: I’m the CEO of Splice Machine.) The first is bringing real-time updates to Hadoop-based analytics applications. Splice Machine has enabled clients to stream real-time data into their databases, and have the secondary indices used for fast lookup to be updated consistently in real-time as well.

      The second is replacing existing RDBMS systems, like Oracle, MySQL or PostgreSQL, that are having trouble scaling. These clients still need transactional capabilities as well as SQL, and Splice Machine has allowed them to maintain both features at scale.

      I would agree that the on-ramp to Hadoop is often an analytical applications, but transactions are going to be a critical requirement for these apps and the operational applications that follow.