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Is Your Data Relational? Expand / Collapse
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Posted Monday, December 2, 2013 11:36 AM
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lshanahan (12/2/2013)
I think this snippet from the MongoDB article sums it up nicely:

This was ultimately a communication problem rather than a technical problem. If these conversations had happened sooner, if we had taken the time to really understand how the client saw the data and what they wanted to do with it, we probably would have done the conversion earlier, when there was less data, and it was easier.


I'll be good and spare everyone the inevitable "Cool Hand Luke" reference...


Due to this being the day after a long holiday, I just saw this. My last post pointed to "skills" as being either pure technical or what I referred to as poor planning skills. To me, technical projects require technical planning skills, not just day to day planning skills. Technical projects are unique.

Back to fire fighting...


Dave
Post #1518970
Posted Monday, December 2, 2013 11:51 AM
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I work with Mongo daily, as well as MSSQL and MySQL and it's really just a question of understanding the strengths and weaknesses of each technology. Mongo is a less mature technology, in terms of the database itself, and supporting tools, but even more so in terms of developer understanding. Developers have spent decades writing to data stores (RDBMS) that had built in guarantees of data quality and consistency that they didn't have to think about much. The headache of mapping objects to normalized tables encapsulated the challenges of keeping the data consistent.

In mongo (or other document centered db's) you have to think about these problems up front. That's the new headache. You will denormalize. You will probably have to denormalize more than you planned to support different use cases. User centric versus feed centric in the linked article. And you need to plan how you are going to keep these in sync. If you need 100% referential integrity, then mongo et al are probably not your best choice. If you can deal with somewhat dirty data and performance or shardability are more important to your application, then mongo may be a better fit.

The real gotcha that I see is that often these choices aren't being driven by a rigorous look at the pro's and cons, but instead by engineering fashion. And that's when mistakes happen.
Post #1518977
Posted Tuesday, December 3, 2013 3:28 AM
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All technologies were immature once.

If your data looks like a document then use a document store. When it looks like a relational dataset use a relational store.

You can get off the ground and running with MongoDB at low cost and when it no-longer fits the bill migrate to something more appropriate and probably costly.

I was intrigued to see PostGres HStore mentioned. It seems to address a large number of concerns that MongoDB would be used for.


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Post #1519145
Posted Tuesday, December 3, 2013 5:00 AM


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I work with both MSSQL & MongoDB. Please excuse me if I am repeating what was already said above.

My frustration is the same as other DBAs supporting MongoDB. Those that do not understand MongoDB, attempt to use it like a relational database. They are surprised & upset that when I inform them that standard functionality to a relational database, is not available in MongoDB. They some how in there minds think that if the software calls its self a database, that it has a minimal set of functionality (mostly what is common in relational database).

In my experience, MongoDB has worked an excellent document database. Again, it is a document not a relational database.
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