It is often said that technology moves at a blazing pace. It's true that there is an ever growing
list of new technologies and techniques being released. However, I've long been of the
opinion that the fundamental technologies used by programmers move at a rather slow pace.
One could spend years learning little yet remain relevant. What is striking though is the speed
at which established technologies get replaced. Seemingly over-night, long established technologies
find themselves threatened by shifts in developer focus.
Nothing could be more representative of this sudden shift than the progress of NoSQL technologies
against well-established relational databases. It almost seems like one day the web
was being driven by a few RDBMS' and the next, five or so NoSQL solutions had established
themselves as worthy solutions.
Even though these transitions seem to happen overnight, the reality is that they can take
years to become accepted practice. The initial enthusiasm is driven by a relatively small set
of developers and companies. Solutions are refined, lessons learned and seeing that a new
technology is here to stay, others slowly try it for themselves. Again, this is particularly true
in the case of NoSQL where many solutions aren't replacements for more traditional storage
solutions, but rather address a specific need in addition to what one might get from traditional
offerings.
Having said all of that, the first thing we ought to do is explain what is meant by NoSQL. It's
a broad term that means different things to different people. Personally, I use it very broadly
to mean a system that plays a part in the storage of data. Put another way, NoSQL (again,
for me), is the belief that your persistence layer isn't necessarily the responsibility of a single
system. Where relational database vendors have historically tried to position their software as
a one-size-fits-all solution, NoSQL leans towards smaller units of responsibility where the best
tool for a given job can be leveraged. So, your NoSQL stack might still leverage a relational
databases, say MySQL, but it'll also contain Redis as a persistence lookup for specific parts of
the system as well as Hadoop for your intensive data processing. Put simply, NoSQL is about
being open and aware of alternative, existing and additional patterns and tools for managing
your data.
You might be wondering where MongoDB fits into all of this. As a document-oriented database,
Mongo is a more generalized NoSQL solution. It should be viewed as an alternative to relational
databases. Like relational databases, it too can benefit from being paired with some of the
more specialized NoSQL solutions. MongoDB has advantages and drawbacks, which we'll cover
in later parts of this book.
As you may have noticed, we use the terms MongoDB and Mongo interchangeably.