While the astronomical growth in data volumes gets most of the attention in Big Data discussions, all that data has no value without fast analysis that drives actionable insights. Action, writes Wikibon Principal Research Contributor Jeff Kelly, is what creates the business value from Big Data. And in this increasingly digitized age, the opportunities are often fleeting. Companies have created entire businesses in areas like advertising technology based on the ability to make split-second business decisions.

While Hadoop is ideal for storing and processing very large volumes of data affordably, it is not well-suited for real-time operational analytics. To do that requires in-line analytics with in-memory databases like Aerospike, DB2 with BLU Acceleration, Pivotal’s Gemfire, Oracle’s Database In-Memory, and SAP’s HANA. These and other in-memory databases are not necessarily new, but the fast dropping price of memory is making them more accessible to businesses when the benefit of very fast performance outweighs the cost of storage data in DRAM.

In-memory databases and Big Data platforms such as Hadoop play by complementary rules. The latter is good for deep data analytics, scouring huge volumes of historical data from multiple sources to discover hidden patterns and insights. Both are important and provide value, but, writes Kelly, in-line analytics supported by in-memory databases is where the real money is made.

Kelly’s full Professional Alert is available without charge on the Wikibon Web site. IT professionals are invited to register for free membership in the Wikibon community, which allows them to comment on published research, post questions and original research and participate in Wikibon research.

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