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Major Differences Between Relational and Non-Relational Databases
Relational databases store data in tables that can be linked through common fields, and they use structured query language (SQL) for querying and managing data. Non-relational databases, on the other hand, store data in a flexible format like documents, key-value pairs, or graphs, and do not require a predefined schema.
When to Use a Relational Database:
- For complex queries and reporting: Relational databases are ideal for situations that involve complex joins, aggregations, and reporting requirements.
- Transactions and ACID compliance: Relational databases offer strong ACID compliance for ensuring data integrity in business-critical applications.
- Structured data: When the data has a well-defined schema and relationships between entities, a relational database is a good choice.
When to Use a Non-Relational Database:
- Scalability and performance: Non-relational databases are more scalable and can handle large volumes of data and high throughput with ease.
- Flexible schema: Non-relational databases are suitable for applications where the data model is likely to evolve over time or where the schema is not fixed.
- Unstructured or semi-structured data: Non-relational databases are well suited for storing unstructured or semi-structured data like JSON documents or key-value pairs.
Database administrators should consider the specific requirements of their applications and choose the type of database that best suits their needs based on these differences.
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