Introduction

• Data is a collection of facts such as numbers, descriptions, and observations used to record information.

  • Structured data - tabular schema

  • Semi-structured data - JSON

  • Unstructured data - documents, images, audio and video, and binary files.

Relational Databases a.k.a. SQL Databases

• designed in the 1970s

• a table-based relation data structure that defines and manipulated data using pre-defined schemas to determine its structure.

• used to store and query structured data.

• follows ACID property which makes it capable of performing different tasks as a single logical operation.
• Examples - MySQL, Microsoft SQL Server, MariaDB, Oracle

• not suitable for frequently changing data

• not flexible due to its rigid pre-determined structure

• difficult to scale as the data increases so the app size increases as well

• are horizontally scalable making them more expensive than non-relational databases

Non-Relational Databases a.k.a. NoSQL Databases

Key-Value databases

• Example - Redis

Document databases

• Examples - MongoDB, Couchbase

Column Family databases

Graph databases

• Example - Neo4j

• can handle the storage of structured and semi-structured data due to its non-tabular form.

• are horizontally scalable making them cheaper than relational databases.

• can make multiple databases with different structures and syntax.

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