The history of IT is one of silos and specialties.
Software programmers, server admins, networking personnel, application managers, database admins, and storage professionals existed almost independently of one another – or at least they attempted to. In the past, it wasn’t much of an issue.
Coding was typically done for specific hardware, such as a mainframe.
But these days, it seems that some developers have been brainwashed by the commodity server mantra.
In the age of virtualization, they hear over and over about the commoditization of hardware.
This leads them to consider that a server is a server. It’s just the same as any other physical server. What does it matter, then, what a newly created application runs on? If the coding is good, all will be well.
That’s the kind of logic you listen to from time to time – and it’s flawed.
It’s Time for the Software and Hardware World to Collide
The fact is that developers are putting their reputations and their projects at risk if they leave hardware decisions in the hands of others. Hardware matters!
Regardless of where the hardware is or how it’s hosted, developers shouldn’t settle for their software being run on outdated or inadequate hardware.
Developers need to guard against any attitude of hardware indifference they may have adopted or any attempt to operate in a software-only bubble.
After all, many of us cut our teeth in environments where the software and hardware worlds rarely collided. We simply developed the application, provided minimum hardware specs, and moved on to the next project.
In the current era of cognitive business, the applications development team and the systems operations team can no longer afford to live in separate universes. They must come together to build applications that work for systems and systems that work for their intended environments.
Combining the latest servers with modern databases can make a big difference in terms of applications running much faster and processing greater amounts of data.
In fact, the right technology combo can change the way companies do business. Developers must lead the charge toward analytics acceleration, data-centric design, open architecture, application optimization, security, and total system scalability.
Enhanced Collaboration Leads to Better Business Outcomes
Let’s look at how this might play out in the real world. With the right database solution backed by the ideal hardware, the dream of high-functioning and highly-available applications becomes a reality.
Developers and systems operations teams would collaborate effectively.
Instead of planning and working alone, they act as a team with shared goals. Only then can they hope to arrive at a holistic solution that leverages the best hardware, software, database, and application development tools to forward the goals and strategies of the business.
For example, the latest graph databases such as Neo4j have the ability to scale up to billions of nodes.
As such, they can deal with massive data volumes, as well as rapidly generate insights within that data store.
So just as you wouldn’t try to run a high-end gaming application on a Chromebook, it is a mistake to hand a Neo4j app over to the hardware guys to dump on whatever platform they happen to have.
Think about it. You spend months perfecting an application that runs with a graph database only to see it sit on a Vanilla X86 server?
Yes, these servers are more powerful today than they have ever been. But you are likely throttling the IO and overall performance of your application and Neo4j.
Bring Power to the Applications You Build
It’s a bit like trying to operate a skyscraper on a generator purchased from Home Depot.
You’ll probably power up a few apartments, but what about the other 50 floors?
It’s the same with graph databases and their associated apps.
To properly harness the magnitude of analytical capability they possess, you have to find the right home—and that is Linux on IBM Power Systems and POWER8 processors.
Collaboration between Neo4J and IBM means that the world’s most scalable graph database platform can be stored entirely in-memory – even if it amounts to billions of nodes. This makes it possible to store and process huge graphs in real time to address problems that were previously unsolvable.
Read more about how Linux on IBM Power and Neo4J make it possible to store and process massive-scale graphs in real time.