Hadoop is all the rage, it seems. With more than 150 enterprises of various sizes using it -- including major companies such as JP Morgan Chase, Google and Yahoo -- it may seem inevitable that the open-source Big Data management system will land in your shop, too.
But before rushing in, make sure you know what you're signing up for. Using Hadoop requires training and a level of analytics expertise that not all companies have quite yet, customers and industry analysts say. And it's still a very young market; a number of Hadoop vendors are duking it out with various implementations, including cloud-based. (See sidebar at left.)
Most important, perhaps: Don't buy into the hype. Forrester Research analyst James Kobielus points out that only 1% of U.S. enterprises are using Hadoop in production environments. "That will double or triple in the coming year," he expects, but caution is still called for, as with any up-and-coming technology.
To be sure, Hadoop has advantages over traditional database management systems, especially the ability to handle both structured data like that found in relational databases, say, as well as unstructured information such as video -- and lots of it. The system can also scale up with a minimum of fuss and bother. eBay, the online global marketplace, has 9 petabytes of both structured data on clusters from Terabyte as well as unstructured data on Hadoop-based clusters running on "thousands" of nodes, according to Hugh Williams, vice president of experience, search and platforms for the company.
"Hadoop has really changed the landscape for us," he says.
"You can run lots of different jobs of different types on the same hardware. The world pre-Hadoop was fairly inflexible that way," Williams explains. "You can make full use of a cluster in a way that's different from the way the last user used it. It allows you to create innovation with very little barrier to entry. That's pretty powerful."
Scaling up, and up
One early Hadoop adopter, Duluth, Ga.-based Concurrent, sells video-streaming systems. It also stores and analyzes huge quantities of video data for its customers. To better cope with the ever-rising amount of data it processes, Concurrent started using Hadoop CDH from Cloudera two years ago.
"Hadoop is the iron hammer we use for taking down big data problems," says William Lazzaro, Concurrent's director of engineering. "It allows us to take in and process large amounts of data in a short amount of time."
One Concurrent division collects and stores consumer statistics about video. That's where Hadoop comes to the rescue, Lazzaro says. "We have one customer now that is generating and storing three billion [data] records a month. We expect at full rollout in the next three months that it will be 10 billion records a month."
Two key limitations for Concurrent in the past were that traditional relational databases can't handle unstructured data such as video and that the amount of data to be processed and stored was growing exponentially larger. "My customers want to keep their data for four to five years," Lazzaro explains. "And when they're generating one petabyte a day, that can be a big data problem."