Relational Database · Interview knowledge

Relational databases are based on the relational model, which organizes data into tables with rows and columns

- Structured data organization
- Relationships and referential integrity: The relationships between tables in a relational database are defined by primary and foreign keys, ensuring referential integrity. This feature allows for efficient querying of related data and supports complex data relationships.
- SQL support: Relational databases use Structured Query Language (SQL) for querying, manipulating, and managing data. SQL is a powerful and widely adopted language that enables developers to perform complex queries and data manipulations.
- Transactions and ACID properties: Relational databases support transactions, which are sets of related operations that either succeed or fail as a whole. This feature ensures the ACID properties – Atomicity, Consistency, Isolation, and Durability – are maintained, guaranteeing data consistency and integrity.
- Indexing and optimization: Relational databases offer various indexing techniques and query optimization strategies, which help improve query performance and reduce resource consumption.
- Limited scalability: Scaling relational databases horizontally (adding more nodes) can be challenging, especially when compared to some NoSQL databases that are designed for distributed environments.
- Rigidity: The predefined schema in relational databases can make it difficult to adapt to changing requirements, as altering the schema may require significant modifications to existing data and applications.

Referenced by

PostgreSQL. Strengths: transactions, joins, constraints, flexible queries. Weaknesses: horizontal scale/sharding complexity, not ideal for huge analytical scans. DynamoDB. Strengths: massive scale, predictable low-latency key access, operational simplicity. Weaknesses: access-pattern-driven modelling, limited relational…

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