In the past few months I’ve had several clients reach out about migrating to In-Memory OLTP solutions. When the second or third request rolled in I remember thinking, “Finally!” As in, I’ve been wondering why businesses haven’t been looking to implement In-Memory sooner. In fact, I added a section on In-Memory to our IEPTO2 course because with the availability of the feature in SQL Server 2016 SP1 (yes, there are memory limitations, but it’s a good place to start) I figured we would see an uptick in interest. But here we are, half way through 2017 and over 6 months since the release of SQL Server 2016 SP1, and I still see a lot of hesitation around it.
I wrote a post over on SQLPerformance last week, Testing DML Statements for In-Memory OLTP, and that generated some discussions on Twitter. So I figured it was time for a post to find out what’s holding companies back. This isn’t a true poll – it’s a fill-in-the-blank. As in: post a comment. If you have considered migrating to In-Memory and then didn’t, I want to understand why. I recognize there are limitations – the product is still new and it’s evolving. But perhaps if we understand the largest inhibitors to migration we can help move them up on Microsoft’s list via Connect and other pathways. Understand I am asking for specifics here, for example: we can’t use In-Memory tables because they don’t support spatial data types. Whatever the reason, share it via a comment.
If I were to take a wild guess, the most common answers will be something like:
- Not using SQL Server 2014 EE or later, or any edition of 2016 SP1 or later
- Limitations in what memory-optimized tables provide: can’t go cross-database, can’t create useful constraints, etc.
- Syntax troubles, particularly in 2014: no outer joins, etc.
- Difficulties fitting this into a legacy system: it’s not just as simple as drop-and-replace tables due to limitations above. Also, due to size limits (none of that NVARCHAR(MAX) business), candidate tables might need to be broken up or restructured so that they fit the mold.
I like using memory-optimized tables where I can, but have had much more success with memory-optimized table-valued parameters.