Are Cubes Dead?

I was talking with a friend recently about technology. This individual is a person focused on business intelligence, originally a developer, but now an architect and consultant. They have a fair number of clients and have worked with them to build solutions to assist in analysis and decision-making for all sorts of organizations. This person has primarily worked in the Microsoft stack but has embraced NoSQL, Hadoop, and other technologies. In many ways they view the world as I do, using what works well for a particular situation without prejudice. They want to be effective, using whatever technology may be best in the current situation.

In their career, this person has extensive SQL Server Analysis Services experience and has built many cubes over the years that clients access with any number of front-end tools. I would guess that cube design and construction have made this person a lot of money over the years.

As we talked, I wasn’t surprised to hear my friend say they thought cubes were dead. It was an approach to analysis that they wouldn’t recommend anymore. That is something I’ve felt for some time. As data volumes grow and competition increases, there is a need for more real-time analysis. The processing time for cubes doesn’t make sense.

Hardware advances, query technologies against files in data lakes, and automatic ingestion of large volumes of data into columnar formats have reduced the need for data mart cubes. I see less and less content produced in this area, both by vendors and individuals working with technology. ETL has given way to ELT, and data lakes seem to be far more useful than data marts that pre-aggregate data in predefined ways.

Most of you reading this work in the OLTP space, but there are plenty of you that built BI solutions or interact with those that need them. In the modern, 2020s era, do you find people still building new cubes and taking advantage of ROLAP/MOLAP/HOLAP systems? Or is this now legacy tech you can’t wait to remove from your infrastructure? I think BI is more important than ever, but cubes are dead.

Steve Jones

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2 Responses to Are Cubes Dead?

  1. b5lurker says:

    I would agree that Multi-Dimensional cubes are not the way to go for a new project today. Microsoft has pretty much stopped investing in SSAS MD cubes and there is no equivalent in Azure for running them native there.

    I would say that Models are still very much alive and well though! To be more specific these are the Tabular Models that Microsoft first started many years ago on-premises with SSAS alongside MD cubes, but it is now used everywhere in Excel, Power BI, Dynamics 365 and more. Models have developed into something far more lightweight than cubes, but just as powerful if not more. The processing issues are being addressed with incremental refresh and hybrid tables and the DAX language to query them is far easier to learn than MDX.


    • kaysauter says:

      I disagree to the point that DAX is easier than MDX. Sure, some concepts are easier but I’ve made the experience that DAX can be very hard, too. Some concepts are even easier in MDX than DAX.
      I agree though: cubes are dead and tabular model is very much alive. I don’t think ELT makes sense in every case; sometimes they certainly do but i believe for a DWH, in perhaps most of the cases, I’d still use ETL. If i can, I’d implement it on Azure, but that’s a different topic again.


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