In memory data warehouse or no?

Question

I have to create a data warehouse (a star schema) and customer wants it in SQL 2014 in memory. My understanding is in-memory has lot of limitations with FK constraints, indexes etc. These are crucial for us, because our fact table volume are in millions. As an alternative I was thinking suggesting creating bunch of de-normalized tables and join them in SQL for reporting and not go with Kimball DWH. I have around 9 transaction and 4 master tables.

Any better suggestion or alternative to go around this?

Answer 1

Normally when you say in-memory with SQL Server, it means the in-memory oltp (Hekaton), which is designed for specific situations, mainly to handle bottlenecks in locking and latching. I would assume that in this case that's not what you mean.

Microsoft also uses in-memory name with clustered columnstore , which to my mind at least makes things quite confusing. Clustered columnstore is designed for data warehouses, and instead of normal row based approach, it stores the data in column format. If you have enterprise edition, it's at least worth trying for fact tables. You should get significant space savings when comparing to normal compressed tables (my fact tables shrunk between 75% - 90% compared page compressed row store) -- which of course helps a lot in terms of what fits into the cache and performance should be a better too, but of course a lot depends on your data, database structure and your queries.

There are quite many restrictions too, biggest ones probably being that you can't have unique indexes or primary / foreign keys. This restriction will be removed in SQL Server 2016, so if you can wait until that, or possibly upgrade once it's available, that might not be such a big issue.

You mentioned that there is no support for indexes. That is true, but you don't need other indexes with clustered columnstore, because the data is stored in column format and is highly compressed.