Start-Up Adds Real-Time Features To Hadoop
Nodeable’s new cloud service analyses streams of data in real time, and speeds up Hadoop deployments
San Francisco-based Nodeable, which started up in 2011 as a Twitter-like notification service for systems management, has made a pivot in its business strategy, and has moved into the market for for helping Apache Hadoop become more user-friendly.
Nodeable has refined its product and is now offering a new cloud service for processing and analysing streams of data in real time, co-founder and chief executive Dave Rosenberg told eWEEK.
The service is designed to address one of Hadoop’s weaknesses, that it works on its own time, offline, and cannot offer results in any sort of real-time scenario.
The service, called StreamReduce, runs on top of Twitter’s open source Storm framework and serves as a much-faster Hadoop front end. It also works with other batch-processing engines, such as Amazon Web Services Elastic Map Reduce.
“For almost a year, the engineering team at Nodeable has worked closely with more than 400 beta users who’ve told us that a real-time analytics complement to Hadoop is a top priority,” Rosenberg said. “Batch workflows are too slow for turning data into useful, actionable information. StreamReduce solves that problem with a simple cloud-based solution.”
Using StreamReduce, IT managers can gain immediate insights into their big data using Hadoop processing, giving users the benefits of on-the-spot analysis of their data streams.
Nodeable beta users can deploy StreamReduce for a variety of use cases, including log and clickstream analysis; anomaly detection in Amazon Web Services EC2 instances; security and fraud detection; mobile and geo-location measurement; pinpointed advertising and marketing.
Nodeable’s StreamReduce service is available now, Rosenberg said, with pricing starting at $99 (£63) per month.
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