In-Memory Computing Adoption

There is no question that data is infiltrating our world. Recently 451 Research predicted that the Total Data Market is expected to double in size from $60 billion in 2014 to $115 billion in 2019.

IDC suggested that Internet of Things (IoT) spending will reach $1.7 trillion in 2020. and noted, “the real opportunity remains in the enterprise…”

And as stated in a recent Gartner blog post, while the three leading independent Hadoop distribution players measure their revenue in 10s of millions, commercial database vendors like Oracle, Microsoft, IBM, SAP and Teradata measure revenues in billions or 10s of billions of dollars in a $33 billion dollar market.

The data market is hot, and in-memory delivers the capabilities companies need to keep up. In the report Market Guide for In-Memory DMBS, published December 2014, analysts Roxane Edjlali, Ehtisham Zaidi, and Donald Feinberg outline the growing importance of in-memory.

Four Reasons for the popularity and adoption of In-Memory

Declining costs in memory and infrastructure

Server main memory (now called server-class memory) is expanding to sizes as high as 32TB and 64TB at an increasingly lower cost, thereby enabling new in-memory technologies such as IMDBMSs, because many applications’ working sets fit entirely into this larger memory. This rapid decline in the infrastructure and memory costs results in significantly better price/performance, making IMDBMS technology very attractive to organizations.

Growing importance of high-performance use cases

The growing number of high performance, response-time critical and low-latency use cases (such as real-time repricing, power grid rerouting, logistics optimization), which are fast becoming vital for better business insight, require faster database querying, concurrency of access and faster transactional and analytical processing. IMDBMSs provide a potential solution to all these challenging use cases, thereby accelerating its adoption.

Improved ROI promise

A cluster of small servers running an IMDBMS can support most or all of an organization’s applications, drastically reducing operating costs for cooling, power, floor space and resources for support and maintenance. This will drive a lower total cost of ownership (TCO) over a three- to five-year period and offset the higher total cost of acquisition from more expensive servers.

Improved data persistence options

Most IMDBMSs now offer features for supporting “data persistence,” that is the ability to survive disruption of their hardware or software environment. Techniques like high availability/disaster recovery (HA/DR) provide durability by replicating data changes from a source database, called the primary database, to a target database, called the standby database. This means that organizations can continue to leverage IMDBMS-enabled analytical and transactional use cases without worrying about prolonged system downtime or losing their critical data to power failures.

From Market Guide for In-Memory DBMS, Roxane Edjlali, Ehtisham Zaidi, Donald Feinberg, 9 December 2014

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