Hadoop Adoption Proves Slow But Steady
A survey of 107 attendees at the recent O’Reilly Strata conference conducted by Dimensional Insight on behalf of Rainstor, a provider of database technology that runs natively on Hadoop, finds that while the adoption of Hadoop in the enterprise is proceeding steadily, there are significant challenges that need to be overcome.
Issues surrounding how long it takes to get a Hadoop application into production coupled with a lack of real-time capabilities are proving to be important barriers to deployment. As a result, the respondents are reporting that both the number of Hadoop applications and the size of the overall Hadoop environment remain relatively small.
What Is Hadoop? Hadoop is a framework made of a variety of components that allows for the distributed processing of large data sets across a fault-tolerant cluster of servers. The core Hadoop project includes Hadoop Common, the utilities that support the other Hadoop modules; Hadoop Distributed File System, a distributed file system that provides high-throughput access to application data; Hadoop YARN, a framework for job scheduling and cluster resource management; and Hadoop MapReduce, a YARN-based interface for parallel processing of large data sets.