Windows 2016 Storage Spaces Direct + Data Deduplication

Has anyone combined S2D (Storage Spaces Direct) with Data Deduplication?

Is this even possible or recommended practice?

Please elaborate on why this is a good idea or not.

EDIT: Just stumbled across this article https://blogs.technet.microsoft.com/filecab/2016/01/05/new-support-for-windows-server-data-deduplication-in-limited-local-hyper-v-configurations/ in regards to Server 2012 R2. It does mention Server 2016, but at the time it wasn't fully released. There's also more info on S2D as well as Data Deduplication on Server 2016 - here https://technet.microsoft.com/en-us/windows-server-docs/storage/storage but not much information on using the two together. It seems based on the first url that they have limited functionality when used at the same time.

Solution 1:

Agreed with Chopper, with Storage Spaces dedupe working as it should be. I'm not sure about S2D right now because it is raw. Microsoft improving S2D day by day, so I think it should work. Improvements you can see from this topic. https://blogs.technet.microsoft.com/filecab/2017/01/30/windows-server-2016-data-deduplication-users-please-install-kb3216755/

Solution 2:

This table straight from Microsoft answers my question.

source:https://technet.microsoft.com/en-us/windows-server-docs/storage/refs/refs-overview

Yes, you could pair S2D with NTFS, but Microsoft has made it pretty clear that ReFS would be the best choice for a S2D deployment.

From the same microsoft url:

"Storage Spaces Direct

Deploying ReFS on Storage Spaces Direct is the recommended setup for virtualized workloads:

Real-time tier optimization and the cache in Storage Spaces Direct deliver high performance and capacity-efficient storage. The introduction of block clone and sparse VDL dramatically accelerates .vhdx file operations, such as creation, merge, and expansion. Built-in checksums, online repair, and alternate data copies enable ReFS and Storage Spaces Direct to jointly to detect and correct corruptions within both metadata and data. ReFS provides the functionality to efficiently scale and support massive data sets."