Databases are the backbone of modern software systems, storing and managing data across virtually every application domain. From traditional relational systems that power banking and e-commerce to specialized vector databases enabling AI applications, choosing the right database type directly impacts performance, scalability, and development velocity. Understanding the landscape—relational, NoSQL, NewSQL, specialized systems, and cloud-native platforms—is critical because each category optimizes for different trade-offs in consistency, availability, query capabilities, and operational complexity. In 2026, the boundary between categories continues to blur as most leading systems adopt multi-model capabilities and AI-native features.
What This Cheat Sheet Covers
This topic spans 19 focused tables and 109 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.
Table 1: Relational Databases (RDBMS)
The workhorses of structured data—these systems organize everything into tables with rows and columns, enforce schemas, and speak SQL. They are the default choice for transactional systems where consistency and well-defined relationships matter, from banking ledgers to e-commerce orders. The names here range from enterprise heavyweights like Oracle and SQL Server to the open-source pillars MySQL and PostgreSQL.
| Database | Example | Description |
|---|---|---|
SELECT * FROM employees WHERE dept_id = 10 | • Enterprise-grade RDBMS with advanced features like partitioning, RAC clustering, and comprehensive PL/SQL support • dominant in large organizations. | |
CREATE TABLE users (id INT PRIMARY KEY, name VARCHAR(100)) | • World's most popular open-source RDBMS • known for ease of use, replication, and widespread community support across web applications. | |
SELECT jsonb_column->>'key' FROM table WHERE id = 1 | • Most advanced open-source RDBMS • supports JSONB, full-text search, advanced indexing, and extensibility via custom types and functions. |