Difference between SQL and NoSQL
|
Key |
SQL |
NoSQL |
|
Type |
SQL databases are classified as Relational Databases (RDBMS). |
NoSQL databases are referred to as Non-Relational or Distributed Databases. |
|
Query Language |
SQL uses the standardized Structured Query Language (SQL), a powerful and widely adopted language for executing complex queries. |
NoSQL databases use dynamic and flexible query languages. The syntax varies depending on the database type (e.g., document, column, graph, key-value). |
|
Scalability |
SQL databases scale vertically—by upgrading server resources such as RAM, CPU, or SSD on a single machine. |
NoSQL databases scale horizontally, meaning new servers can be added to handle increased load. This makes NoSQL ideal for large-scale, dynamic applications. |
|
Schema Design |
SQL databases use a fixed, predefined schema. Changes to the schema require significant planning and may disrupt operations. |
NoSQL databases use a schema-less design, offering flexibility to store various types of data and easily adapt to evolving requirements. |
|
Internal Architecture |
SQL systems are based on ACID properties (Atomicity, Consistency, Isolation, Durability), ensuring strict data integrity and transactional reliability. |
NoSQL systems follow the CAP theorem (Consistency, Availability, Partition Tolerance), optimizing for performance and scalability in distributed environments. |
|
Data Storage |
SQL databases store data in tables with rows and columns, best suited for structured, multi-row transactional applications. |
NoSQL databases support various storage models such as document-based, key-value pairs, column-oriented, and graph databases, enabling hierarchical and distributed data storage. |
|
Data Type |
Ideal for structured data with relationships among entities—useful for financial systems, CRM, and enterprise applications. |
Better suited for semi-structured or unstructured data, such as user-generated content, multimedia, or real-time feeds. |
|
Performance and Use Case |
SQL databases excel at complex querying and transactional accuracy, but they may struggle with high-volume, hierarchical data. |
NoSQL databases offer high performance with massive volumes of dynamic data, although they’re generally less powerful for complex queries. |
|
Examples |
Popular SQL databases include both open-source and commercial tools: MySQL, PostgreSQL (open source) and Oracle, SQLite (commercial). |
Common NoSQL databases include MongoDB, Redis, Cassandra, HBase, CouchDB, Neo4j, BigTable, and RavenDB, most of which are open-source. |