SQL and NoSQL Databases
Welcome to this guide on SQL and NoSQL databases. This collection of documents provides a comprehensive overview of the fundamental concepts behind both relational (SQL) and non-relational (NoSQL) database systems.
Overview
In the world of data management, the choice of database technology is a critical architectural decision. This guide explores the two major paradigms:
SQL (Relational Databases)
For decades, relational databases have been the standard for data storage. They are built on the principles of the relational model, organizing data into structured tables with rows and columns. This section covers:
- Fundamentals: What a relational database is, its pros and cons, and core concepts like records, fields, and data types.
- SQL (Structured Query Language): The standard language for interacting with relational databases. We will explore essential commands for retrieving, filtering, sorting, grouping, and joining data.
- Data Integrity: Concepts like ACID properties, primary keys, and normalization that ensure data is reliable and consistent.
- Practical Application: A look at how to use SQL with Python's built-in
sqlite3library.
NoSQL (Non-Relational Databases)
With the rise of big data and large-scale web applications, NoSQL databases have emerged as a powerful alternative. They offer more flexibility and scalability than their relational counterparts. This section delves into:
- Core Concepts: What "Not Only SQL" means, and the key characteristics like schema-less design and horizontal scalability.
- The CAP Theorem: A fundamental principle (Consistency, Availability, Partition tolerance) that governs distributed data stores.
- ACID vs. BASE: A comparison of the transactional models that underpin SQL and NoSQL databases.
- Modern Solutions: An overview of different NoSQL implementations and their use cases in cloud environments.