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Binary Data

Here Come In-memory Databases

While most enterprise data still resides in traditional relational databases, demand for in-memory databases continues to grow — particularly within midmarket businesses that are seeking faster compute capabilities for big data applications.

A case in point: Approyo expects its customer base for SAP’s HANA to reach roughly 75 businesses by the close of this year — up from about 65 disclosed in May. (ChannelE2E is seeking a sales update from Approvo.) SAP HANA is an in-memory, column-oriented relational database management system. It’s designed for real-time business intelligence systems.

In the meantime, the initial sales estimate included a heavy dose of midsize customers. “We are continuing to see the landscape of SAP HANA change with recent mergers and acquisitions, especially in the midmarket” said Marcus Retrac, president of Approyo, in a prepared statement earlier this year.

Approyo and SAP certainly aren’t alone in the market. Demand for in-memory computing systems is expected to reach $13.23 billion by 2018 — a compound annual growth rate (CAGR) of 43 percent from $2.21 billion in 2013, according to Markets and Markets.

Eager to cash in, traditional database partners — working with IBM, Microsoft, Oracle, SAP and others — have been tipping their toes into the in-memory database market. Moreover, new partners have been signing up to work with MemSQL and other in-memory database upstarts.

Still, it’s unclear if or when the in-memory approach will overtake the traditional database market. Indeed, market research suggests most enterprise data continues to reside in traditional databases like Microsoft SQL Server and Oracle — without any in-memory enhancements or changes.

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