NoSQL (Not Only SQL) is an approach to database design that provides high—speed and flexible data management that is not possible with traditional SQL databases.
The NoSQL Revolution
The NoSQL revolution was driven by necessity. When big data and web applications that worked in real time appeared, traditional SQL databases with their rigid schemas and scaling constraints began to lose their relevance. NoSQL databases, capable of working with unstructured data and scaling horizontally, have become the optimal solution to modern data problems.
Types of NoSQL databases
NoSQL databases come in different types, each with its own unique capabilities and applications. The four main types are:
- document databases such as MongoDB store data in a semi-structured format, such as JSON, which makes them ideal for working with various types of data;
- key value stores such as Redis provide high performance and are ideal for storing information about sessions, user profiles and preferences;
- broadband storage, such as Cassandra, is optimized for querying large amounts of data and is used in analytics;
- Graph databases such as Neo4j do an excellent job of storing interconnected data, making them an ideal solution for social media.
Comparative analysis of NoSQL and SQL
NoSQL databases provide high scalability, flexibility when working with unstructured data and high speed. However, SQL databases still have an advantage when it comes to ACID transactions (Atomicity, Consistency, Isolation, Durability) and support for standardized languages.
Using NoSQL
NoSQL databases have found their niche in various industries. Tech giants such as Google, Facebook, and Amazon use NoSQL for their data-intensive applications. NoSQL is also widely used in real-time analytics, content management, and IoT applications.