Weaknesses in Traditional Data Platforms
Everyone understands that Hadoop brings high performance commercial computing to organizations using relatively low cost commodity storage. What is accelerating the move to Hadoop are weaknesses in traditional relational and data warehouse platforms in meeting today's business needs. Some key weaknesses of traditional platforms include: Late binding with schemas greatly increase the latency between receiving new data sources and deriving business value from this data. The significantly high cost and complexity of SAN storage. This high cost forces organizations to aggregate and remove a lot of data that contains high business value. Important details and information are getting thrown out or hidden in aggregated data. The complexity of working with semi-structured and unstructured data. The incredible cost, complexity and ramifications of maintaining database administrators, storage and networking teams in traditional platforms. There are lo...

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