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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.

Key Differentiator: Splice Machine claims to have the only transactional SQL-on-Hadoop database that powers real-time big data applications.

6. DataTorrent

What They Do: Provide a real-time stream processing platform built on Hadoop.

Headquarters: Santa Clara, Calif.

CEO: Phu Hoang, who was previously a founding member of the engineering team at Yahoo, where he served as executive vice president of engineering.

Founded: 2012

Funding: The company closed an $8 million Series A round in June 2013. August Capital led the round and was joined by AME Cloud Ventures. The company previously secured $750K in seed funding from Morado Ventures and Farzad Nazem.

Why They're on This List: DataTorrent argues that we'll soon start thinking about latency issues when we think about Big Data solutions. DataTorrent points out that "data is happening now, streaming-in from various sources — in real-time, all the time." Many organizations struggle to process, analyze, and act on this never-ending and ever-growing stream of information — at all.

For some insights, by the time data is stored to disk, analyzed, and responded to — it's already too late. For instance, if a hacker compromises a credit card account and manages to make a few purchase, plenty of damage has already been done, even if that account is cut off within minutes. DataTorrent contends that an organization's ability to recognize and react to events instantaneously isn't just a business advantage. In today's word, it is a necessity.

Unlike traditional batch processing that can take hours, DataTorrent claims to be able to execute hundreds of millions of data items per second. This enables organizations to process, monitor, and make decisions based on their data in real-time.

Competitive Landscape: DataTorrent's main competitors come from IBM (Infosphere Streams) and the Storm Open Source Project.

Key Differentiator: DataTorrent points to performance as a key differentiator, claiming their platform is 100-1,000 times faster than Storm.

7. Qubole

What They Do: Offer Big Data-as-a-Service with a "true auto-scaling Hadoop cluster."

Headquarters: Mountain View, Calif.

CEO: Ashish Thusoo, who ran Facebook's data infrastructure team before co-founding Qubole. He also co-founded Apache Hive.

Founded: 2011

Funding: The company is backed by $7 million in Series A funding from Lightspeed Ventures and Charles River Ventures.

Why They're on This List: Since Hadoop is a relatively new technology, finding someone with the expertise necessary to run and maintain it can be a tall order. By providing a managed solution, Qubole hopes to make Hadoop an easy-to-use technology.

Qubole handles the initial setup and then maintains the clusters. Qubole's auto-scaling feature automatically spins up users' clusters when a job is started and automatically scales or contracts based on workload, cutting back on costs and management requirements.

 

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