Hewlett Packard Enterprise defines in-memory computing as a method of achieving better performance from data processing by storing it in memory rather than cached on disk. In-memory computing is an old idea, but in recent years it has come to the fore because of the added demands on database infrastructure to keep up with ever-burgeoning data stores.

The earliest attempts at in-memory computing happened in the early 1990s according to Datanami but dealt solely with small data sets. Today's in-memory databases can hold billions of rows of data and are used to generate insights from this data that business operators can use to adapt their business to challenges better. While in-memory computing is a prevalent approach to database processing and storage, business owners can look at this technological benefit from two different perspectives.

Perspective 1 - Powerful Computing That Does Everything

One of the largest providers of business database solutions in the world is SAP. Statista estimates that there were around 10,500 users of SAP's S/4 HANA globally in 2018. There's no question that SAP is one of the most potent processing suites out there for a corporate environment. Additionally, because of the full range of businesses that use it, SAP has proven to be quite adaptable with third-party providers offering software packages that can be integrated with the base system. SAP S/4 HANA is the cloud-based system that makes up the latest offering that SAP has for its users. SAP boasts that HANA has the potential to do real-time analytics of large data stores and makes it an impressive offering to business customers who are thinking about implementing Big Data Analytics, IoT or both.

SAP has shown that it's an optimized system, but one of the things it excels at might be the one thing that lowers its value in the overall scheme of things - the options it offers the customer. SAP is a technical suite of software that requires someone versed in it to operate appropriately. For a company to know what it needs and where it should spend its money in acquiring SAP modules, it needs to have a clear idea of where it is as a business and where it intends to be. Additionally, it usually requires a dedicated team of technicians to ensure that upgrades are pushed out on time and that downtime doesn't affect the business on the whole. The sheer volume of choices can be overwhelming to all but the largest (or most ambitious) corporate bodies. Additionally, because of the complex nature of SAP's processing, it usually requires someone to digest its analytics and present it in a report that's readable by regular humans.

Perspective 2 - Computing That Fits User Needs and Speaks to users Directly

Lesser-known, but an earlier adopter of the in-memory computing technique, QlikView represents a more user-friendly software interface that business users can use to generate analytics about their company. While QlikView isn't able to perform the same raw processing tasks that SAP can do, it has something else that SAP doesn't - a human-readable output combined with a human-logical method of presenting results. A paper presented by Universidad Austral mentions that QlikView tries to show results that are comparable to how the human mind sees data. How QlikView manages to do that is by utilizing a technology known as associative architecture.

How QlikView achieves this is by using an associative data engine - a system by which they can effectively analyze each data point in reference to each other to develop insights that a human mind would come up with eventually. QlikView offers a system that not only allows clients to run their queries but offers suggestions about questions that a user should have asked along with the results of those queries. The result is database software that is fast, efficient, and almost does all the thinking for you. The appeal for many business owners is a combination of practical insights as well as a system that doesn't need a substantial additional IT staff on call to operate regularly. In terms of scalability, QlikView might be better for a smaller company because of what it does and what it requires to function.

Value for Time and Money

The discussion of whether the first or second perspective is better depends on how a company sees its data stores. Smaller companies have fewer eyes on their data and need as much help as they can get to be able to compete in the market. Larger companies can take a broader scatter-shot approach, selecting the avenues they prefer to follow and ignoring others. While in the case of an SAP install, a company can look at all the available branches they can go down and start pruning, in the case of QlikView, it's a matter of taking the suggestions as they appear. There's no "right" way to do data analytics aside from the implementation that offers the most relevant insight to the user, and both systems have their own ways of doing so. The inherent value of in-memory technology is not just providing understandable insights to the business owner, but doing so at the right time to make crucial business decisions.