![]() ![]() MySQL often gets blamed for poor performance. This is probably pretty scary to MySQL experts, but if you continue reading, you'll see there is a place for both MySQL and MongoDB. This means you have to optimize your schema based on how your application will access the data. In MongoDB, you have to use embedding and linking instead of joins and you don't have transactions. The idea is not to prefer any specific application pattern. In MySQL there is really isn't much flexibility in how you structure your data if you follow normalization standards. You just drop in documents, and two documents within a collection don't even need to have the same fields. One of my favorite things about MongoDB is that you don't define the schema. MySQL requires you to define your tables and columns before you can store anything, and every row in a table must have the same columns. MongoDB does not support transactions, but single operations are atomic. The ability to contain multiple operations within a transaction and roll back the whole thing as if it were a single operation. TransactionsĪnother great thing about MySQL is its support for atomic transactions. In MongoDB you might have a single collection of posts, and an array of comments within each post. For example, if you were to create a blog using MySQL, you would have a table for posts and a table for comments. Placing one document inside another is referred to as embedding. MongoDB does not support joins, but it does multi-dimensional data types such as arrays and even other documents. This allows you to perform queries across multiple tables. One of the best things about MySQL and relational databases in general is the almighty JOIN operation. If you're already familiar with SQL, it'll take a little bit of time to wrap your brain around this concept, but once you figure it out, it feels a lot more intuitive. By that I mean you pass it a document to explain what you are querying for. This is what makes SQL injection attacks possible. That's because you have to put together a string in this query language that is parsed by the database system. The SQL in MySQL stands for Structured Query Language. If you're using python, its just like a dictionary object. If you're using PHP, it's just like an associative array. If you are using javascript, it's exactly what you're working with. If you think about it, a JSON document is very much like what you would be working with in your application layer. ![]() MongoDB represents data as collections of JSON documents. MySQL represents data in tables and rows. Let's look at some of the differences between MongoDB and a relational system like MySQL. Since then, many alternative database systems have been released. Thankfully, we never jumped on to the ORM bandwagon. In fact, it's so inefficient that it just about killed relational database systems altogether. The problem, however, is that this is horribly inefficient and it teaches developers to ignore how the underlying database works. It lets you access relational data in a way that is convenient for your application. ![]() Fast forward a few years, and just about every web application framework out there implements an ORM layer. At first appearance, this might seem delightfully convenient, and to some extent it is. Instead of writing queries with joins, you can access related data through properties of an object.įor example, if you have a "post" object that represents a blog post, you can access it's comments through the property "ments". That means that instead of writing a query to insert or update a record, you assign some properties to an object and call a save method. An ORM layer basically provides an object oriented interface to a relational database. What you might not know, is that it also popularized ORM (Object-Relational Mapping) layers with its ActiveRecord object. It was back in 2004 that Ruby on Rails first came out and popularized web application frameworks. Here's a quick guide on the differences between MySQL (Relational) and MongoDB (Non-Relational / NoSQL). When building a custom web application you need to consider the type of database that best suits the data. ![]()
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