Two friends, Tom and Lisa, were out at a nightclub having a great time. It was a special night of dancing, eating, and drinking, and everyone was having the time of their life.
At midnight, Tom said, “I have to leave now.”
“Is there an emergency?” Lisa asked.
“No, I have to go do my laundry.”
Lisa was shocked. “Did you just say you need to leave this great party to do your laundry? Why now? Why not wait until tomorrow?”
Tom explained that he did his laundry at a laundromat, and if he waited until Sunday the place would be crowded and he would be lucky to get one washing machine and would be there all day. But if he did his laundry at midnight on a Saturday, the laundromat would be empty and he could use all eight washing machines and then all eight dryers and be done in an hour and a half.
That is parallel processing!
Why parallel processing matters
What Tom has done is essentially parallel processed all of his parallel processing systems (in this case, washing and drying machines). And the strategy works in business, too.
The biggest roadblock in the computer industry has been the fights of Microsoft versus Oracle and Teradata versus IBM. These fights have become even more competitive with the success of cloud dominators Microsoft Azure and Amazon AWS clouds. Netezza doesn’t talk to Redshift and DB2 doesn’t talk with Vertica. Every vendor hates one another, but data has become so large that no one vendor can be used to store it all.
Multiple vendors and multiple systems are used by almost every major corporation for a wide variety of reasons. This can create a lot of confusion and inefficiency. The best solution is for a company to parallel process their many parallel processing systems as if they were all one giant system.
Parallel processing across systems doesn’t mean that everyone has access to all data. Each database has security and access rights to objects so data can be protected, and users can still only access data they have been given permission to query. But the real point is that users can be granted access to data from many systems and join that data together efficiently, quickly, and easily.
Use Nexus for simplified parallel processing
The best way to parallel process is with the Nexus Query Chameleon software on the desktop and NexusCore Servers strategically placed between different systems.
Nexus on the desktop has 15 years of intelligent coding and millions of lines of artificial intelligence so performing data movement and cross-system joins is so easy that anyone can do it. The NexusCore Servers also have the same 15 years of intelligent coding and millions of lines of artificial intelligence, with some additional logic so they can impersonate a user’s credentials and create a universal scheduling calendar.
Nexus on the desktop can move data from one system to another by converting the table structures and data types from one system to almost any other system in seconds. Its brilliance shines even more because it knows how to build data movement scripts that are understood by each system so moving data between systems is as easy as point-and-click and move.
Finally, Nexus on the desktop is so intelligent that it can show tables and views from all systems and allow users to merely drop-and-drag or use the join menu to join data, with Nexus building the SQL with each click of the mouse. It almost can’t get any easier, but almost nobody else has figured out how to do it.
The NexusCore Server can do everything the desktop Nexus can do, but it has a special purpose. When users want to move data between systems or perform cross-system joins it is magnitudes of order faster and more efficient to initiate this from the server, rather than the user’s laptop. Nexus on the desktop allows the user to create the cross-system joins or choose what data they want to move between systems, but it’s the server that impersonates the user’s credentials and initiates the work as if the user was sitting at the server themselves. How clever is that?
If your company has parallel processing systems, then it makes sense to parallel process all your parallel processing systems together! To learn more, schedule a demo with me see Nexus in action.