RDBMS:
🔵Data Structure: Organizes data into structured tables with rows and columns.
🔵Schema: Fixed and predefined; requires data normalization.
🔵Query Language: SQL (Structured Query Language) for managing and retrieving data.
🔵Scalability: Generally scaled vertically, which can be costly.
🔵Integrity: Enforces data integrity through ACID properties and relational constraints.
🔵Examples: MySQL, PostgreSQL, Oracle.
NoSQL:
🔴Data Structure: More flexible, handling a wide range of data types with dynamic schemas.
🔴Schema: Schema-less or with a flexible schema; allows for denormalization.
🔴Query Language: No declarative query language; uses various methods depending on the system.
🔴Scalability: Designed for horizontal scalability, often at a lower cost.
🔴Integrity: Data consistency varies depending on the NoSQL type; may not strictly enforce ACID properties.
🔴Examples: MongoDB, Cassandra, Redis, Couchbase.
In essence, RDBMS is well-suited for applications requiring complex queries and strict data consistency, while NoSQL excels in scenarios demanding scalability, flexibility, and handling of varied data types
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