Migrate SSAS Olap to the Elasticsearch


I work at a company that is thinking about migrate his BI structure ( SSAS Olap and Power BI ) to the ElasticSearch. Our BI work basically with aggregations as sum, max, min, first, last, average at aggregation in multiples hierarchy levels( organization level, customer level, unit level, etc...), and expressions between multiples measures( getting by aggregation and find first/last based on datetime ) like sum, subtraction, multiplication, division, percentage. We work with more than 1 billion rows at total. Before SSAS Olap we worked with SQL Server OLTP, and our queries were taking many minutes. Because that, we change to OLAP and we now have our aggregate measures in a few seconds. But the Microsoft License is bursting our new budget. At the moment, our Business Intelligence solution doesn't have data mining, neither machine learning, only aggregations measures at multiples hierarchy levels, and operations between these aggregations.

And our solution is the entire on-premises.

I have 2 questions:

1-With the free/basic Elasticsearch license, we will be able to migrate our business intelligence solution to the ElasticEngine and do all these hierarchies, aggregation and search in multiple levels operations?

2-With the free/basic Elasticsearch engine, we will have these measures aggregations between these millions registers and operations between measures at a similar time as our OLAP cube?

Best Regards,


It sounds like Elasticsearch will do most of what you are looking for, and much faster and cheaper.

It might be best to put a subset of your data into it and the play round to see if it can offer everything at the level of ease you want.


Thank you for your answer. Elasticsearch will do all this even using the free license? The BI software without license cost is one of our new requirements, because that I would like to emphasize this part.

Best Regards,

I think it'll do a lot of it, yes. Like I said, you should test it.


Thank you again for the answer. I have a last question, one thing that happens in our database is that some dimension rows in our OLTP receive update operations some times( example: customers data as identification ); but our dimensions table have few rows( between hundreds and thousands rows ). This could be a problem in Elasticsearch?

Updating in Elasticsearch is relatively expensive compared to a SQL database.
However if you aren't updating thousands of documents a minute you will be fine.

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