On-Premises or Cloud: Which Is the Right Platform for Big Data Analytics?

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Click to learn more about author Mathias Golombek.

Security and performance are vital if you want Big Data Analytics, as it usually involves security-sensitive applications that have to cope with ever-increasing amounts of data. And there are countless case studies that show that a proven way to do this is with on-premises implementation together with an in-memory database. Not to mention the benefit of being able to install a solution on your existing hardware, giving you full control over your own data and enabling you to integrate it with other existing applications and databases.

But Is the Cloud Better for Strategic Thinking?

A separate on-premises data center may be ideal for operating an in-memory database, but it’s not always the best solution for the overall IT strategy of the entire company. If you think outside of the technical requirement, the cloud offers more flexibility, and is often more cost-effective with demand-oriented billing. Plus, you can reduce the IT administration effort needed, as third-party cloud providers take over both maintenance and updating.

But all of this is irrelevant if your chosen cloud isn’t set up for data analytics. One of the most important features of an in-memory database is that it includes analytics tools that are cloud-ready. This is the only way to ensure that Big Data Analytics can be flexibly adapted to the changing requirements of your organization. And if you already use a cloud solution such as Amazon Web Services, Google Cloud, or Microsoft Azure, the most strategic thing you can do is find an in-memory database that enables you to do your analytics with what you already have – with no costly implementations or changes to your infrastructure.

Choose a Solution to Fit Your Strategy – Not the Other Way Around

We don’t want to sit on the fence here, but really, it all comes down to what you are trying to achieve with your data analytics and above that the big strategic idea that’s driving all this analysis in the first place. One man’s hybrid cloud is another woman’s on-premises nightmare.

Ultimately, if you’re a decision maker, you need to ask yourself the following three fundamental questions:

  1. How much flexibility does the IT infrastructure require? Big Data Analytics that constantly operate under a full load do not necessarily need to be able to scale flexibly up and down.
  2. Can the cloud really reduce costs for you? The answer to this question varies greatly depending on the specific application.
  3. How dependent is your organization on the services of a particular cloud provider? If you have vendor lock-in, make sure the database is set up for that vendor.

Inevitably, the answers to these questions may vary over time. That’s why we believe the key is finding an in-memory database with both on-premises and cloud operation, at best even in parallel and on different platforms. This will give you maximum flexibility for a data strategy today, tomorrow, and in the future.

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