2. SQL Versus NoSQL & MongoDB Basics

NoSQL (“non SQL” or “not only SQL”) databases were developed in the late 2000s with a focus on scaling, fast queries, allowing for frequent application changes, and making programming simpler for developers. Relational databases accessed with SQL (Structured Query Language) were developed in the 1970s with a focus on reducing data duplication as storage was much more costly than developer time. SQL databases tend to have rigid, complex, tabular schemas and typically require expensive vertical scaling.

The five critical differences of SQL vs NoSQL:
SQL databases are relational, NoSQL are non-relational.
SQL databases use structured query language and have a predefined schema. NoSQL databases have dynamic schemas for unstructured data.
SQL databases are vertically scalable, NoSQL databases are horizontally scalable.
SQL databases are table based, while NoSQL databases are document, key-value, graph or wide-column stores.
SQL databases are better for multi-row transactions, NoSQL are better for unstructured data like documents or JSON.

What are the Benefits of NoSQL Databases?

NoSQL databases offer many benefits over relational databases. NoSQL databases have flexible data models, scale horizontally, have incredibly fast queries, and are easy for developers to work with.

Flexible data models

NoSQL databases typically have very flexible schemas. A flexible schema allows you to easily make changes to your database as requirements change. You can iterate quickly and continuously integrate new application features to provide value to your users faster.

Horizontal scaling

Most SQL databases require you to scale-up vertically (migrate to a larger, more expensive server) when you exceed the capacity requirements of your current server. Conversely, most NoSQL databases allow you to scale-out horizontally, meaning you can add cheaper, commodity servers whenever you need to.

Fast queries

Queries in NoSQL databases can be faster than SQL databases. Why? Data in SQL databases is typically normalized, so queries for a single object or entity require you to join data from multiple tables. As your tables grow in size, the joins can become expensive. However, data in NoSQL databases is typically stored in a way that is optimized for queries. The rule of thumb when you use MongoDB is Data is that is accessed together should be stored together. Queries typically do not require joins, so the queries are very fast.

Easy for developers

Some NoSQL databases like MongoDB map their data structures to those of popular programming languages. This mapping allows developers to store their data in the same way that they use it in their application code. While it may seem like a trivial advantage, this mapping can allow developers to write less code, leading to faster development time and fewer bugs.

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