Table of Contents

Database Types

NoSQL Databases

• These databases are designed to handle a wide variety of data types, including column stores, document stores, graph databases, and key:value stores. They are particularly suited for handling large volumes of structured, semi-structured, and unstructured data. NoSQL databases are often used in big data applications and real-time web apps due to their flexibility, scalability, and performance.

Document Stores

• Document-oriented databases store and manage data as a collection of documents rather than rows or columns in a table. These documents are usually JSON-like data structures that can contain nested structures. This model is highly flexible and is often used in content management systems and applications requiring high flexibility for each record.

Graph Databases

• Graph databases are designed to store entities and their relationships in a graph format. They are particularly useful for applications that require intensive relationship-driven queries, such as social networks, recommendation engines, and fraud detection systems.

Columnar Databases

• Columnar databases store data in columns rather than rows, which is beneficial for analytics and business intelligence where operations often involve computing aggregates over large numbers of similar data items. This structure allows for better compression and efficient IO operations.

Object-Oriented Databases

• These databases store data in the form of objects, as used in object-oriented programming. Object-oriented databases are used in applications where data needs to be stored in a way that is consistent with the programming model, eliminating the need for a relational mapping layer.

Distributed Databases

• Distributed databases manage data across multiple machines to ensure reliability, scalability, and availability. They are particularly effective in handling very large data sets and high transaction volumes across different locations.

Time-Series Databases

• These are optimized for handling time-stamped data that is generated continuously by sensors, IoT devices, financial systems, and monitoring tools. Time-series databases are built to store, retrieve, and process time-based data efficiently.

Blockchain Databases

• Blockchain technology offers a decentralized database solution where data integrity, verification, and trust are maintained through cryptography, consensus algorithms, and transactional ledgers. This is particularly useful in applications that require immutable records, like supply chain, finance, and contract management.