MongoDB vs MySQL vs Redis: What are the differences?

Key Differences between MongoDB, MySQL, and Redis

MongoDB, MySQL, and Redis are three popular database management systems, each with its own unique features and capabilities. Understanding the key differences between them is crucial for making an informed decision when it comes to selecting the right database for your specific use case.

1. Data Model and Structure: MongoDB is a NoSQL database that follows a document-based data model. It stores data in flexible, JSON-like documents that can have varying structures. MySQL, on the other hand, is a relational database management system (RDBMS) that stores data in tables with predefined schemas. Redis acts as a key-value store, where values can be a variety of different data types.

2. Scalability and Performance: MongoDB offers horizontal scalability out of the box, thanks to its ability to shard data across multiple servers. This makes it well-suited for handling large amounts of data and high traffic loads. MySQL, on the other hand, relies on vertical scalability, which involves upgrading the hardware of a single server. Redis is known for its exceptional performance, often beating both MongoDB and MySQL in terms of throughput and latency.

3. Query Language and Flexibility: MongoDB uses a flexible query language called the MongoDB Query Language (MQL), which allows for complex queries and supports various operators and aggregation functions. MySQL uses Structured Query Language (SQL), which is a standardized language for managing relational databases. Redis, being a key-value store, primarily supports simple read and write operations without complex querying capabilities.

4. Data Consistency: MongoDB provides eventual consistency by default, meaning that after writing to a document, a certain amount of time may pass before the data propagates to all replicas. MySQL, on the other hand, provides strong consistency, ensuring that all replicas have the latest data after a write operation. Redis offers different data consistency options, including eventual consistency, strong consistency, and even strong eventual consistency with the use of additional modules.

5. Transaction Support: MongoDB introduced multi-document ACID transactions starting from version 4.0, allowing developers to perform complex operations that span multiple documents. MySQL has had support for transactions since its early days, making it reliable for maintaining data integrity in complex operations. Redis traditionally lacked full transaction support but has added support for transactions using the MULTI and EXEC commands.

6. Use Cases and Application Scenarios: MongoDB is often favored in scenarios where flexibility, scalability, and real-time analytics on unstructured or semi-structured data are required, such as content management systems and Internet of Things (IoT) applications. MySQL is commonly used in applications that require strict data consistency, complex relationships between entities, and stringent ACID compliance, such as e-commerce platforms and financial systems. Redis finds its strength in use cases that demand high-speed data caching, real-time analytics, message brokering, and pub/sub scenarios.

In summary, MongoDB offers a flexible, horizontally scalable document-based data model, while MySQL provides robust relational capabilities with strong consistency. Redis excels in performance-critical scenarios and offers versatile data types. The choice between them depends on specific requirements, such as data structure, scalability needs, querying capabilities, transaction support, and application use cases.