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How In-Memory Computing can be an ERP Game-changer – the 3 Questions to Ask

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Rick Veague, Americas CTO at IFS, weighs up the pros and cons of in-memory computing and outlines the three questions that companies looking to integrate need to ask

There is a lot of enthusiasm for in-memory computing for business, but it can be difficult to cut though all the noise to get to the true significance of the technology. What is in-memory computing? And how can it improve the performance of ERP and other enterprise-wide transactional systems?

As the name implies, in-memory computing replaces data stores held in disc-based tables and runs it instead in the random access memory (RAM) of a computer or cluster of computing resources in the cloud. In-memory computing is widely used for a number of things outside of an enterprise application—real time streaming and analysis of enormous quantities of transactions across social media, for instance.

An ERP application that harnesses the power of in-memory computing may differ from these ‘pure’ in-memory applications in a few ways. ERP with in-memory features will preserve the traditional database traits of atomicity, consistency, isolation and durability (ACID) that are there to guarantee you can trust the integrity of the transaction. These traits are typically abandoned in other in-memory systems. ERP with in-memory features may also differ from pure in-memory applications in that they have both an in-memory and a disc-based database. This enables the application to select which portions of a transactional database to move to memory while the remainder of the database remains disc-based to preserve RAM.

Here, I’ve outlined three important questions to ask when thinking about considering in-memory computing as part of your ERP strategy.

1. How will this speed up my querying and reporting?

The main benefit is enhanced processing speed.  Data stored in-memory can be accessed hundreds of times faster than would be the case on a hard disc – which is important for businesses dealing with larger data sets and non-indexed tables that need to be accessed immediately.

Within ERP, this speed is particularly useful when companies are running ad-hoc queries, say, to identify customer orders that conform to specific criteria or determine which customer projects consume a common part. Enterprise software run with traditional disc-based storage is likely to bog down if the database running business transactions in real-time is also responding to regular queries from the business intelligence systems.

But an in-memory application should be, in a manner of speaking, a type of hybrid solution between RAM and disc-based storage. In theory, a pure in-memory computing system will require no disc space. But this is impractical since a modern enterprise applications can store both structured and unstructured data such as photos, technical drawings, video and other materials that are not used for analytical purposes – but would consume a great deal of memory. The benefit of moving imagery – for example, photos an electric utility engineer may take of meters – in-memory would be minimal and the cost high. This data is not queried, does not drive visualizations or business intelligence and would consume substantial memory resources.

A hybrid model containing both a traditional and in-memory database working in sync enables the end-user to keep all or part of the database in-memory, so that columns and tables that are frequently queried by business analytics tools or referenced in ad hoc queries can be accessed almost instantly. Meanwhile, data that doesn’t need to be accessed as frequently is stored in a physical disc, enabling businesses to get real-time access to important information while making the most of their current IT systems.

2. Why do software vendors have different reasons for liking in-memory than buyers?

The incentives that drive a company to adopt in-memory computing are straightforward. Some large enterprises may be harnessing big data from social media and other online sources and harvesting insights from an in-memory data set. But for many industrial companies, the most compelling case for in-memory technology may stem from the need of senior managers to view aggregated enterprise data in real-time.

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