reDocument-Level Optimistic Concurrency in MongoDB

time to read 2 min | 313 words

I run into this blog post talking about how to handle optimistic concurrency in MongoDB and it brought to mind a very fundamental difference in the design philosophy between RavenDB and MongoDB.

If you’ll read the associated blog post, you’ll see guidance on how to build a simple optimistic concurrency using the MongoDB API. It looks like a relatively straightforward thing, but there is a lot of complexity going on here.

With RavenDB, we have decided that the responsibility of such tasks is on us, and not our users. Here is how you’ll write the same thing in RavenDB:

session.Advanced.OptimisticConcurrency = true;

And you are done. There are also options to set it globally (for all actions), for a particular session, as shown above or for a particular document or documents in a bigger transaction. About the only thing that we don’t handle is retries if the update failed, to allow you to re-run your business logic.

The reason I’m writing this is actually at the very end of the post:

This works just fine if I "remember" to include that Where clause correctly, but there's a better way if we want a general solution. For that, I'd do pretty much what I would have in the Life Beyond Distributed Transactions series - introduce a Repository, Unit of Work, and Identity Map.

This is exactly right. It looks trivial to do something like that when you are looking into a trivial scenario, but put it in a real application and the complexity sprouts. For example, try doing the same thing with multiple documents that need to change together. You have to implement quite a lot of code to do so (identity map, unit of work, hopefully not a repository Smile).

With RavenDB, all of that is just there and available for you. No need to do anything, It Just Works.

More posts in "re" series:

  1. (23 Jun 2021) The performance regression odyssey
  2. (27 Oct 2020) Investigating query performance issue in RavenDB
  3. (27 Dec 2019) Writing a very fast cache service with millions of entries
  4. (26 Dec 2019) Why databases use ordered indexes but programming uses hash tables
  5. (12 Nov 2019) Document-Level Optimistic Concurrency in MongoDB
  6. (25 Oct 2019) RavenDB. Two years of pain and joy
  7. (19 Aug 2019) The Order of the JSON, AKA–irresponsible assumptions and blind spots
  8. (10 Oct 2017) Entity Framework Core performance tuning–Part III
  9. (09 Oct 2017) Different I/O Access Methods for Linux
  10. (06 Oct 2017) Entity Framework Core performance tuning–Part II
  11. (04 Oct 2017) Entity Framework Core performance tuning–part I
  12. (26 Apr 2017) Writing a Time Series Database from Scratch
  13. (28 Jul 2016) Why Uber Engineering Switched from Postgres to MySQL
  14. (15 Jun 2016) Why you can't be a good .NET developer
  15. (12 Nov 2013) Why You Should Never Use MongoDB
  16. (21 Aug 2013) How memory mapped files, filesystems and cloud storage works
  17. (15 Apr 2012) Kiip’s MongoDB’s experience
  18. (18 Oct 2010) Diverse.NET
  19. (10 Apr 2010) NoSQL, meh
  20. (30 Sep 2009) Are you smart enough to do without TDD
  21. (17 Aug 2008) MVC Storefront Part 19
  22. (24 Mar 2008) How to create fully encapsulated Domain Models
  23. (21 Feb 2008) Versioning Issues With Abstract Base Classes and Interfaces
  24. (18 Aug 2007) Saving to Blob
  25. (27 Jul 2007) SSIS - 15 Faults Rebuttal
  26. (29 May 2007) The OR/M Smackdown
  27. (06 Mar 2007) IoC and Average Programmers
  28. (19 Sep 2005) DLinq Mapping