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Big Data is Everywhere & Growing. Forever changing how customers and businesses interact, enabling new opportunities.
With the Internet now touching two billion people daily, every call, tweet, e-mail, download, or purchase generates valuable data. Companies are increasingly relying on Hadoop to unlock the hidden value of this rapidly expanding data, and to drive increased growth and profitability. Experienced users understand the challenges and limitations presented by Hadoop. While there is currently a choice of six different Hadoop distributions, they all share the same configuration issues, single points of failure, data loss risks, and performance limitations. The MapR Distribution for Apache Hadoop adds innovation to the excellent work already done by a large community of developers. With key new technology advances, MapR transforms Hadoop into a dependable and interactive system with real-time data flows.
Compounding the challenge is that much of this new data is unstructured. Many businesses, for example, now want to analyze more complex high-value data types (such as clickstream and social media data, as well as un-modeled, multi-structured data) to gain new insights. The problem is, these new data types do not fit the existing massively parallel processing model that was designed for structured data in most data warehouses. The cost to scale traditional data warehousing technologies is high and eventually becomes prohibitive. Even if the cost could be justified, the performance would be insufficient to accommodate today’s growing volume, velocity, and variety of data. Something more scalable and cost-effective is needed, and Hadoop satisfies both of these needs. Hadoop is a complete, open-source ecosystem for capturing, organizing, storing, searching, sharing, analyzing, visualizing, and otherwise processing disparate data sources (structured, semi-structured, and unstructured) in a cluster of commodity computers. This architecture gives Hadoop clusters incremental and virtually unlimited scalability — from a few to a few thousand servers, each offering local storage and computation.