Introduction to SQLSQL DatabaseSQL DatatypesSQL QueriesSQL DML StatementsSQL Constraints and IndexingSQL FunctionsStored Procedure and Triggers
1. Relational Databases (RDBMS)
Relational databases store data in a structured format, using rows and columns in tables. They rely on Structured Query Language (SQL) for querying and maintaining the database.
2. Non-Relational Databases (NoSQL)
Non-relational databases, often referred to as NoSQL databases, do not use the traditional relational model with tables, rows, and columns.
| Feature | Relational Databases (RDBMS) | Non-Relational Databases (NoSQL) |
|---|---|---|
| Data Model | Structured, table-based with rows and columns. | Flexible; can be key-value, document, graph, or column-family. |
| Schema | Fixed schema with predefined structure. | Schema-less or flexible schema. |
| Query Language | SQL (Structured Query Language) | Varies (e.g., MongoDB uses its query language, Graph databases use graph queries). |
| Consistency | Strong consistency (ACID compliant). | Often favors availability and partition tolerance (CAP theorem). |
| Scalability | Vertical scaling (increasing power of a single server). | Horizontal scaling (distributing data across multiple servers). |
| Flexibility | Less flexible, as changes to the schema require migrations. | More flexible, supports unstructured or semi-structured data. |
| Performance | May not perform well with large-scale data, especially unstructured data. | Can perform better with large-scale data and distributed systems. |
| Examples | MySQL, PostgreSQL, Oracle, SQL Server | MongoDB, Cassandra, Redis, Neo4j, CouchDB |
