Why Hadoop?

Divide and conquer: That’s the simple truth of Hadoop. At its core, Hadoop is a distributed file system and distributed MapReduce processing framework that both stores and processes data by dividing workloads across several servers.

incon3Scalable

A cluster can be expanded by adding new servers or resources without having to move, reformat, or change the dependent analytic workflows or applications.

incon4Cost effective

Hadoop brings massively parallel computing to commodity servers. The result is a sizeable decrease in the cost per terabyte of storage, which in turn makes it affordable to model all your data.

incon5Flexible

Hadoop is schema-less and can absorb any type of data, structured or not, from any number of sources. Data from multiple sources can be joined and aggregated in arbitrary ways enabling deeper analyses than any one system can provide.

incon1Fault tolerant

When you lose a node, the system redirects work to another location of the data and continues processing without missing a beat.

Hadoop is unstoppable as its open source roots grow wildly and deeply into enterprise data management architectures. Its refreshingly unique approach to data management is transforming how companies store, process, analyze, and share data of any size and structure. Forrester believes that Hadoop is a must-have data platform for large enterprises, forming the cornerstone of any flexible future data management platform if you have lots of structured, unstructured, and/or binary data, there is a sweet spot for Hadoop in your organization.

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