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10 hot Hadoop startups to watch

Jeff Vance | April 17, 2014
As data volumes grow, figuring out how to unlock value becomes vastly important. Hadoop enables the processing of large data sets in a distributed environment and has become almost synonymous with big data. Here are 10 startups with solutions for unlocking big data value.

To solve this problem, Trifacta uses "Predictive Interaction" technology to elevate data manipulation into a visual experience, allowing users to quickly and easily identify features of interest or concern. As analysts highlight visual features, Trifacta's predictive algorithms observe both user behavior and properties of the data to anticipate the user's intent and make suggestions without the need for user specification. As a result, the cumbersome task of data transformation becomes a lightweight experience that is far more agile and efficient than traditional approaches. Lockheed Martin and Accretive Health are early customers.

Competitive Landscape: Trifacta will compete with Paxata, Informatica and CirroHow.

Key Differentiator: Trifacta argues that the problem of data transformation requires a radically new interaction model — one that couples human business insight with machine intelligence. Trifacta's platform combines visual interaction with intelligent inference and "Predictive Interaction" technology to close the gap between people and data.

5. Splice Machine

What They Do: Provide a Hadoop-based, SQL-compliant database designed for big data applications.

Headquarters: San Francisco, Calif.

CEO: Monte Zweben, who previously worked at the NASA Ames Research Center where he served as the Deputy Branch Chief of the Artificial Intelligence Branch. He later founded and served as CEO of Blue Martini Software.

Founded: 2012

Funding: They are backed by $19 million in funding from Interwest Partners and Mohr Davidow Ventures.

Why They're on This List: Application and Web developers have been moving away from traditional relational databases due to rapidly growing data volumes and evolving data types. New solutions are needed to solve scaling and schema issues. Splice Machine argues that even a few short months ago Hadoop, while viewed as a great place to store massive amounts of data, wasn't ready to power applications.

Now, with emerging database solutions, features that made RDBMS so popular for so long, such as ACID compliance, transactional integrity, and standard SQL, are available on top of the cost-effective and scalable Hadoop platform. Splice Machine believes that this enables developers to get the best of both worlds in one general-purpose database platform.

Splice Machine provides all the benefits of NoSQL databases, such as auto-sharding, scalability, fault tolerance, and high availability, while retaining SQL, which is still the industry standard. Splice Machine optimizes complex queries to power real-time OLTP and OLAP applications at scale without rewriting existing SQL-based apps and BI tool integrations. By leveraging distributed computing, Splice Machine can scale from terabytes to petabytes by simply adding more commodity servers. Splice Machine is able to provide this scalability without sacrificing the SQL functionality or the ACID compliance that are cornerstones of an RDBMS.

Competitive Landscape: Competitors include Cloudera, MemSQL, NuoDB, Datastax, and VoltDB.

 

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