1/31/2024 0 Comments Tabular vs multidimensional![]() But I did have a very strong background in tabular, by way of Excel, and also 25 years with SQL Server development (TDS starts with “tabular”, eh?) I arrived a bit late to the DW world, having only read and observed cubes and multi-dimensional literature. If you’re using Multidimensional, I hope an migration to Tabular is on your road map (cause it should be).If you’re using Tabular, I hope you’re using 2016+ (if not, it’s time to upgrade).What this tells me is that DAXMD (the feature added to SSAS Multidimensional instances allowing them to process DAX queries) has not been updated to handle Super DAX. ![]() Query (4, 5) The function 'SUMMARIZECOLUMNS' is not available for Multidimensional models. I then tried to take the Super DAX query generated for the SSAS 2017 Tabular instance and run it via SSMS against the SSAS 2017 Multidimensional instance and got the following error message: Executing the query. DESC, 'Date', 'Date'Īgainst an equivalent SSAS cube deployed to a SSAS 2017 Multidimensional instance, the same query was generated…which means Power BI did not try to generate Super DAX for the SSAS 2017 Multidimensional instance. KEEPFILTERS ( SUMMARIZE ( VALUES ('Date'), 'Date', 'Date')), That, my friends, why Super DAX is such a big deal!Īgainst an equivalent SSAS cube deployed to a SSAS 2014 Multidimensional instance, we get the following query captured in profiler: EVALUATE …where as the second version of the query (against the 2017 tabular model) results in only 1 storage engine query… Better yet… the first version of the query (against the 2014 tabular model) results in 3 storage engine queries… SUMMARIZECOLUMNS('Date', "Sales_Amount", 'Sale'),Īs you can see, Power BI detected the model compatibility level and generated different DAX queries accordingly. "Sales_Amount_Day", 'Sale'Īgainst a 1400-level model deployed to a SSAS 2017 Tabular instance, we get the following query captured in profiler: EVALUATE Next, I used a very simple Power BI report with a single visual (showing sales amount by day of month) and captured the DAX queries via profiler.Īgainst a 1103-level model deployed to a SSAS 2014 Tabular instance, we get the following query captured in profiler: EVALUATE To test this out, I installed SSAS 2014 Tabular & Multidimensional instances along side the existing SSAS 2017 Tabular & Multidimensional instances and deployed an equivalent SSAS database to each instance. Long story short: Not only does Power BI generate the same DAX queries regardless of the SSAS Multidimensional version… “Super DAX” is NOT supported by any version of Multidimensional instance. In other words, would Power BI generate “Super DAX” against 2016/2017 multidimensional instances? Can 2016/2017 multidimensional models even handle “Super DAX”? ![]() What I wasn’t sure of (and just finished testing) is whether or not the same was true for Multidimensional cubes. That benefit is “Super DAX” ( more info). For folks using Power BI reporting, there’s a pretty significant benefit in reporting against Tabular 1200+ models deployed to a SSAS 2016+ instance as opposed to a Tabular 1103 (and below) model deployed to a SSAS 2014 (and below) instance. ![]() Update 20170825: some enhancements between SSAS MD 2014 to 2016/2016 worth mentioning… improved locking/blocking, memory allocation, heap fragmentation, database consistency checking (DBCC), and 圎vents GUI.Īs the meeting carried on, I started thinking a bit more about that question. That time and effort would be better spent migrating to Tabular 2016+” My initial response was “ no, there would be little benefit in carrying out that upgrade… other than a few more years of support and a couple of random hotfixes. The client wanted to know if there was any benefit for them in upgrading from SSAS 2014 Multidimensional to SSAS 2016 Multidimensional. An interesting question came up during a recent engagement involving Power BI reporting against a Multidimensional data source.
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