One of the biggest shifts in data analytics over the past decade is the move away from building “data cubes”, or “OLAP cubes”, to running OLAP workloads directly on columnar databases. By Cedric Chin.
Online Analytical Processing (or OLAP) is a fancy term used to describe a certain class of database applications. The term was invented by database legend Edgar F. Codd, in a 1993 paper titled Providing OLAP to User-Analysts: An IT Mandate.
-The OLAP cube grew out of a simple idea in programming: take data and put it into what is known as a “2-dimensional array” —-that is, a list of lists.
This is a huge change, especially if you’ve built your career in data analytics over the past three decades. What are the tradeoffs? What are the costs? Is this move really as good as all the new vendors say that it is? And of course, there’s that voice at the back of your head, asking: is this just another fad that will go away, like the NoSQL movement before it? Will it even last?
The article main parts are:
- What the heck is OLAP?
- The performance challenges of OLAP
- The rise of the OLAP Cube
- Wither the OLAP Cube
- A new paradigm emerges
Tech-savy companies like Amazon, Airbnb, Uber and Google have rejected the data cube paradigm entirely; these events and more tell us that we are going to see both trends spread into the enterprise over the next decade. Excellent read!
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