For each of the past three years, Enterprise Management Associates (EMA) has conducted a primary research study directed at the evolution of data management platforms associated with Big Data. These studies have shown that data management platforms supporting Big Data initiatives cannot be pigeon-holed into a technical constraint such as “just” Hadoop… or “just” NoSQL… or “just” historical analytics…or just the data center.

To many long-time enterprise administrators, the idea of a distributed database is unnerving at best. Instead of having all your data, the database platform and the supporting hardware in one place where you can keep an eye on it, the architecture is spread across multiple locations, and almost always on a diverse, heterogeneous footprint.

But as the broader data environment becomes more distributed, it is only natural that the database should as well. And as it turns out, the enterprise has virtually nothing to lose

Seismic shifts in the technology landscape are rare: the rise of distributed client/server computing to displace the mainframe is one. We are currently in the middle of another such shift, the inexorable rise of cloud computing. Anyone who has run an operational computing environment for a large enterprise will know that the sheer complexity of layer upon layer of infrastructure is proving a major constraint to businesses. Each time you want to upgrade an application (or are forced to by a vendor) then you have to consider the

If you ask most CIOs what they want from their database architecture, the usual answer is “performance.”

While speed, scale, flexibility and other metrics are important, they are all factors in the overall performance equation. In the end, users want to do more in less time without it costing an arm and a leg, and this is why so many enterprises are looking to the cloud to take on more of the database load.

At the recent AWS re:Invent conference, Redis Labs released a survey that showed