September 24, 2013


There’s a growing trend for DBMS to beef up their support for multiple data manipulation languages (DMLs) or APIs — and there’s a special boom in JSON support, MongoDB-compatible or otherwise. So I talked earlier tonight with IBM’s Bobbie Cochrane about how JSON is managed in DB2.

For starters, let’s note that there are at least four strategies IBM could have used.

IBM’s technology choices are of course influenced by its use case focus. It’s reasonable to divide MongoDB use cases into two large buckets:

IBM’s DB2 JSON features are targeted at the latter bucket. Also, I suspect that IBM is generally looking for a way to please users who enjoy working on and with their MongoDB skills. 

More technically speaking, IBM is assuming somewhat simpler JSON than might be stored in MongoDB. Notes on that include:

Specifics of IBM’s JSON read/write story in DB2 include:

DB2 also has some capability to traverse JSON, but I’m not clear as to where exactly that kicks in.

*The fenced vs. unfenced distinction for analytic platforms refers to out-of-process vs. in-process execution.

And finally, some of IBM’s choices are easier to understand in the context of a DB2 concept called “side tables”. As best I understand:


2 Responses to “JSON in DB2”

  1. Doug Henschen on September 26th, 2013 5:41 pm

    You’ve told us how they built their watch, but can they tell us what time it is? To ask another way, what types of applications can DB2 now support where JSON is concerned? Just “customer 360 degree view,” as you suggest? As ably as MongoDB is doing for the likes of MetLife?

    Still an interesting read even if it’s more about the how than why.


  2. Curt Monash on September 26th, 2013 6:48 pm

    If the MongoDB compatibility is as good as they say, then the MongoDB applications they couldn’t happen would be questions mainly of performance or scalability. (Other concerns would of course be price, plus ease of installation/administration.)

    That said, if you want to use MongoDB, why use DB2 to emulate it? The natural applications for this capability are ones that MongoDB can’t easily handle, e.g. where you’d like to normalize somewhat and/or use data that’s in an existing relational schema.

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