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Understanding CQRS: Choosing Between Shared and Separate Databases

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Chapter 1: Introduction to CQRS

In this article, we will explore a crucial aspect of Event-Driven Architecture (EDA): the decision between implementing Command Query Responsibility Segregation (CQRS) with a single database or opting for multiple databases.

If you haven't yet reviewed the initial articles in this series, please refer to: - EDA Comprehensive Guide 1: Should You Migrate to Event-Driven Architecture? - EDA Comprehensive Guide 2: Designing System Boundaries Effectively.

Before delving into the database options for CQRS, it’s essential to understand the distinction between Command Query Separation (CQS) and CQRS.

Section 1.1: The Distinction Between CQS and CQRS

CQS, a concept introduced by Bertrand Meyer, suggests that a method should either serve as a command (a "write" operation) that alters the state or as a query (a "read" operation) that retrieves data without modifying it. In simpler terms, a method should focus on one task: either returning a value or altering the state, but not both.

CQS emphasizes the separation of concerns within a single class or object: - Commands: These are methods that change an object's state, such as adding a user or updating an order, and they do not return any value. - Queries: These methods retrieve information without altering the object's state, such as fetching user details or searching for products, and they typically return data.

This clear separation enhances maintainability and clarity in code.

Subsection 1.1.1: Exploring CQRS

CQRS extends the principles of CQS by further separating the responsibilities of command handling (modifying the system) from query handling (retrieving data). Instead of using a single model for both operations, CQRS promotes the use of two distinct models: one for commands and another for queries.

This separation allows for: - Command Model: Focused on data modification, often utilizing a relational database optimized for write operations. - Query Model: Designed for efficient data retrieval, which could involve a NoSQL database or a pre-aggregated materialized view.

This architecture enables independent optimization and scaling of read and write operations.

Section 1.2: CQRS with a Shared Database

Using a shared database for both commands and queries simplifies the implementation, especially in scenarios where separate databases may introduce unnecessary complexity. This approach features: - Separate Models: Distinct models for commands and queries, each tailored for its specific purpose. - Separation of Logic: Clear delineation in the application code to handle commands and queries, which enhances maintainability and minimizes data modification risks during retrieval.

Benefits of a Shared Database: 1. Unified Data Source: A single source of truth simplifies system architecture and reduces management overhead. 2. Lower Maintenance Costs: With no need to synchronize multiple databases, operational costs decrease. 3. Simplicity: Particularly in smaller systems, a shared database can provide adequate performance and scalability without added complexity.

Chapter 2: CQRS with Separate Databases

The first video titled "Shared Database Per Service Design Pattern Tutorial for Microservices with Examples" illustrates the nuances of utilizing a shared database model in microservices architecture. It provides insights into the advantages and considerations of this approach.

Using separate databases for commands and queries represents a more traditional method. This setup often results in distinct physical databases for read and write operations, offering specific advantages.

Features of Separate Databases: - Command Model: Typically a relational database optimized for write operations. - Query Model: Often utilizes NoSQL databases for rapid reads or data warehouses for analytics.

Benefits of Separate Databases: 1. Performance Optimization: The read database can be fine-tuned for quick querying and reporting. 2. Scalability: Enables independent scaling of read operations, leveraging techniques like replication and sharding. 3. Flexibility: Allows for varied storage technologies to be utilized for reads and writes, depending on the system's requirements.

The second video titled "Master Event Sourcing in Just 10 Minutes" offers a concise overview of event sourcing principles, which can complement CQRS strategies in managing data effectively.

Conclusion

The adaptability of CQRS lies in its capacity to cater to the specific needs of a system. Regardless of whether you select shared or separate databases, the fundamental principle of differentiating commands (writes) from queries (reads) remains central. This separation allows for tailored optimization, enhancing performance, scalability, and maintainability.

It is crucial to consider data consistency, especially when opting for separate databases, as this can lead to complexities known as eventual consistency. More on this topic will be covered in future articles.

For further reading, you may find the following articles interesting: - Request-Driven Service vs. Event-Driven Service - EDA Comprehensive Guide 1: Should You Migrate to Event-Driven Architecture? - EDA Comprehensive Guide 2: Effective System Boundary Design - EDA Comprehensive Guide 3: Choosing Between Shared and Separate Databases

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