What is MongoDB and Why is it Important to Everyone ?
MongoDB is a structured way of storing your data which allows for easy access and manipulation.
As engineers, we deal with data everyday and all data must be stored somewhere - hand calcs for instance are stored on sheets of papers, that are shoved away in folders. Equally, calculations can be performed in a digital medium using something like Excel. For years, such media have worked quite well for us in terms of storing (and even help us perform) our engineering designs.
However, in recent years, we've seen that project are becoming more and more complex. The pieces of information, or numbers of calcuations required can run into the tens of millions! Consider that Excel explicitly states that it can only hold 1,048,576 rows by 16,384 columns worth of data - how would you use Excel to deal with 20 million rows of calculations? Even if you were a Excel VBA wizard, how long would it take you to loop through all that data to find the subset of all those rows that contain values in Column F greater than X and less than Y? For anybody who has come across this situation, you will know, whilst it can be done, it is inconvenient and inefficient to perform such a task. Excel was never meant to be a program to handle 2017 'Big Data'.
So the question we must ask is "How will we manage our data in the future?" and if you're reading this Wikipage, you probably have already guess the answer.....MongDB!
When we talk of MongoDB, I want you to think of sieves. Yep, that's right, sieves like these:
When you put your data into MongoDB, its structured behind the scenes to allow you to create elaborate and fancy sieves that you can use to filter and even manipulate your data. This is much like the filtering data in Excel, however, with much more capability on how you can filter and also, because of the structuring of the data, with the ability to perform the filtering on massive databases (recall that its called MongoDB for huMONGOus DataBases......cute, right? Ya, they thought of it not me). Also, as you will see, the structure of the data precludes the need for looping, which simplifies the coding language to set up these programmatic sieves (a huge plus considering most of us engineers are amateurs when it comes to coding). We could easily envisage a database full of data on employee's and how we could filter that data:
Mongo allows us to quickly filter through and transform millions of lines of data, using clear, concise coding language that is easy to understand and debug.