MongoDB vs MySQL

Introduction

For decades, relational database management systems such as MySQL have served as the basis for countless enterprise applications. However, today’s organizations face different challenges than their predecessors, which means they need to find better ways to store and access their data. Enter a new generation of document-oriented, or NosQL, databases, with MongoDB standing out as one of the most popular examples of its kind. If you’re trying to decide between MySQL and MongoDB for your database needs, you may want to learn more about the similarities and differences between these two products. In this article, we’ll take a deeper look at these database management systems and compare MySQL vs MongoDB.

What is MongoDB

Let’s start with a little background information on MongoDB. The idea for MongoDB was initially hatched in 2007 by 10gen Software, though the first version wasn’t released until 2010. Today, MongoDB is free to use and open-source; versions released after October 16th, 2018 are published under the Server Side Public License (SSPL).

While a traditional relational database relies on tables made up of rows and columns, MongoDB stores data as “documents” using a binary form of JSON called BSON. Unlike rows in a relational database, fields can vary among documents– you can add a new field to a single document with no impact on other documents. In fact, you don’t even need to define a particular schema for a document. Documents are “self-describing” in MongoDB, which basically means that the field name and its value are stored in the same place.

MongoDB is a highly scalable database solution due to its “horizontal scaling” approach. This means that capacity is increased by distributing a system’s load and dataset among multiple servers. MongoDB uses an architecture called sharding, where data is partitioned and spread among database instances, to enable horizontal scaling.

What is MySQL

Now that we’ve gotten a basic introduction to MongoDB, let’s turn our attention to MySQL– a relational database management system that was developed and distributed by Oracle. It’s a free, open-source product, available under the GPL license. Like other relational databases that rely on a table structure containing rows and columns, MySQL uses Structured Query Language (SQL) to access the database. SQL is a widely-used, versatile query language that allows users to create complex queries spanning multiple tables. When related information is stored in different tables, JOIN operations are used to correlate the data and query multiple tables at once.

When it comes to scalability, databases that use SQL are “vertically scalable”– you handle increased load by upgrading the CPU, SSD or RAM on a single server. Horizontal scaling is difficult to achieve in relational databases because JOINs become inefficient when tables are spread across different nodes in a cluster.

Why Choose MongoDB?

More and more organizations are choosing non-relational databases like MongoDB for their enterprise applications, and there are some good reasons for that choice. MongoDB’s ability to handle large volumes of unstructured data quickly gives it a significant advantage over MySQL, which can perform more slowly when faced with larger amounts of data. MongoDB is also highly scalable– if you think your deployment is going to grow big, MongoDB will grow with you.

In addition to its scalability and efficient performance, MongoDB also makes it possible to develop applications at a faster rate. This is because MongoDB’s flexible data model maps more naturally to the way data is represented in applications. The ability to add new attributes to documents without having to make changes to a rigid database schema minimizes downtime and allows your data model to evolve with your business needs.

Why Choose MySQL?

Despite the many advantages of MongoDB and other non-relational databases, there are still situations where a relational database like MySQL is the better choice. If you’re looking for a replacement product for legacy applications that were designed around the standard relational model, MongoDB simply isn’t a “drop-in” solution. Legacy applications do need to be modernized in order to work with MongoDB. However, organizations generally find that a migration to MongoDB improves performance in these legacy applications, and the flexible data model helps new applications get built faster in the future.

Summary

At first glance, you may wonder what the differences are between MySQL and MongoDB– after all, they’re both open-source, and they’re both free. However, once you dig a little deeper, the differences become clear. Each of these database management systems has their own respective benefits and drawbacks. Ultimately, the right choice for your organization will depend on the unique requirements of your enterprise application.

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