in memory computing

Approximately two years back I made a post on Enterprise Data Fabric technology. The aim of the data grid or “in memory data store” is to remove the movement of data in and out of slower disk storage for processing. Instead the data in kept in “pooled main memory” during the processing.

To get above the physical limitations on the amount of main memory, the data grid technologies will create a pooled memory cluster with data distributed over multiple nodes connected using a high bandwidth network.

With SAP bringing HANA, an in memory database that has option to store data in traditional row store and column store (read storing data in rows and columns) within an in-memory technology and Oracle bringing the Exaletics appliance, the in-memory computing is getting more attention.

So, the claims are that the in memory technology will boost the performance by multiple degrees. But the truth is it can only remove the time taken to move the data out of disk into main memory. If there is a query that is processing the data using a wrong access method, even if all the data is moved into a memory store the processing will still take as long to provide the answer!

In memory computing would need re designing the applications to use the technology for better information processing. OLTP workload will surely improve the performance due to memory caching but the consistency of the data need to be managed by the application moving to a event based architecture.

OLAP and Analytical workloads would also improve the performance by using memory based column stores with a good design of the underlying structure of data that suits the processing requirements.

Overall, in memory computing is promising at the moment but without the right design to use the new technology, the old systems will not just get the performance boost just by moving the data store into the main memory

Let us wait and see how the technology shapes further in future…..

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