MongoDB for Developers with Python Transcripts
Chapter: High-performance MongoDB
Lecture: Introducing performance-tuning in MongoDB
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Now that you know how to work MongoDB, you know how to work its shell,
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what the query syntax is, you've seen PyMongo as well as MongoEngine,
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it's time to turn our attention to tuning MongoDB
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to be the best database it can possibly be.
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We're going to focus on how to make our regular MongoDB server
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a high performance MongoDB database
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and you'll see there's no magic here, a lot of the things that you can do
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are relatively straightforward, and there's a systematic way to go about it.
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I want to start this section by maybe putting a little perspective on it.
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I want to start this section, this chapter, by putting a little perspective out there.
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When people come to NoSql and they start looking for alternative databases
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often the allure of these databases is their performance
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you hear about things like sharding, horizontally scaling them,
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some incredible performance numbers, things like that.
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That may be what you really need, that may be the most important thing
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and certainly if you don't have performance out of your database it's a big problem.
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We're going to certainly figure out how to make our databases faster
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and the variety of techniques that we have available to us in MongoDB.
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That said, your biggest problem probably isn't performance,
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you may have a big data problem, you may have terabytes or petabytes of data
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but most applications don't.
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You may have a performance problem, it may be that you have so much data
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or you are asking such complex queries that it really does take
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very precise tuning and scaling to make it work.
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So we're going to focus on some of these types of things.
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That said, we all have a complexity problem with our application,
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it's always a pain to maintain these databases
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especially when we're working with relational databases,
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you hear about things like migrations and updating your schema
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adding, removing, transforming columns, all of this stuff is really complex
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and it even makes deployment really, really challenging,
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you want to release a new version of something based on SQLAlchemy
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but you need to change the database scheme before it will even run—
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okay, that sounds like it could be a little bit of a problem.
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What you'll see with MongoDB and these document databases is
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one of their biggest benefits is the simplicity that they bring.
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The document structure means there's fewer tables,
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there is much fewer connections between these tables,
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so when you think about the trade-offs and performance and things like that
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keep in mind that probably the biggest benefit
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that you are going to get from MongoDB is you are going to have
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simpler versioning, evolution, maintainability, development story.
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I just want to put that out there, because I know sometimes
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people will say well, I got MongoDB to perform at this speed
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and I cut this other database, and if I tweak it like this and adapt it like that
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maybe I could get it to go a little faster, so maybe we should use that instead.
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And maybe, I don't know, it depends on the situation,
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and this is very abstract, so it's hard to say, but keep in mind
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that one of the biggest things these document databases
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bring to you to the table here, is this simplicity.
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It just so happens we can also make them really, really fast.
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So simple and fast, sounds like a great combination,
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so let's get into this section where we are going to make MongoDB much faster.
