How do you balance performance and abstraction in your repositories?

Domain-Driven Design (DDD) is a software development approach that focuses on the core domain and business logic of an application. One of the key concepts of DDD is the repository, which is an abstraction layer that provides access to the data sources and hides the implementation details. However, creating a generic and flexible repository interface can also introduce performance issues, such as over-fetching, under-fetching, or unnecessary queries. How do you balance performance and abstraction in your repositories?

1 Understand your domain

The first step to balance performance and abstraction is to understand your domain and its data needs. What are the domain entities, aggregates, and value objects that you need to store and retrieve? How are they related to each other? What are the common operations and queries that you perform on them? By answering these questions, you can design a repository interface that reflects the domain language and behavior, and avoids exposing irrelevant or low-level details.

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2 Choose the right data access strategy

The next step is to choose the right data access strategy for your repository implementation. Depending on your data source, you may have different options, such as using an object-relational mapper (ORM), a query builder, a micro-ORM, or a raw SQL. Each option has its pros and cons in terms of performance, flexibility, and maintainability. For example, an ORM can simplify the mapping between objects and tables, but it can also generate inefficient queries or load unnecessary data. A query builder can give you more control over the SQL, but it can also introduce complexity and duplication. A micro-ORM can offer a balance between simplicity and performance, but it can also limit your capabilities or require more code. A raw SQL can give you the best performance and customization, but it can also make your code harder to test and refactor.

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LukÃ¡Å¡ M.

Software developer ve spoleÄnosti Seznam.cz. ---------- ------------ Backend developer with a passion for #scalability.
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In my experience, it is appropriate to avoid ORMs. While they can simplify life, they often bring unnecessary problems. They tend to be slower due to abstraction, we often don't see how it works under the hood and they can lack of some functionalities. I'm in favor of using raw SQL and keeping everything under control.

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3 Optimize your queries

The third step is to optimize your queries for performance and abstraction. This means that you should write queries that only fetch the data that you need, avoid unnecessary joins or subqueries, use indexes and caching where appropriate, and handle concurrency and transactions properly. You should also use query objects or specifications to encapsulate the query logic and parameters, and avoid leaking them to the repository interface. This way, you can keep your repository interface clean and domain-oriented, and delegate the query execution to the data access strategy.

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LukÃ¡Å¡ M.

Software developer ve spoleÄnosti Seznam.cz. ---------- ------------ Backend developer with a passion for #scalability.
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It's beneficial to use CQRS to separate write and read requests. This relieves the primary database from the load of read queries, allowing you to dedicate it to write operations and improve its performance. You can then forward read requests to multiple read replicas for better scalability and responsivness. Your application receives addresses for both the primary database (write) and the read replicas. This enables efficient routing of requests based on their type. In your code, you can create separate repositories for both write and read operations to maintain clear separation.

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4 Test and measure your performance

The fourth step is to test and measure your performance regularly. You should use tools and metrics to monitor and analyze your data access performance, such as the number of queries, the execution time, the network latency, the memory usage, and the CPU load. You should also use benchmarks and load tests to compare different data access strategies and identify potential bottlenecks or issues. By testing and measuring your performance, you can ensure that your repository implementation meets your expectations and requirements, and make adjustments or improvements if needed.

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5 Apply the principle of least astonishment

The fifth step is to apply the principle of least astonishment to your repository interface and implementation. This means that you should design your repository interface and implementation in a way that does not surprise or confuse the users or consumers of your repository. For example, you should avoid returning null values or empty collections, throwing unexpected exceptions, or modifying the state of the entities or aggregates without explicit consent. You should also document your repository interface and implementation clearly and consistently, and follow the naming and coding conventions of your domain and language.

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6 Review and refactor your repository

The final step is to review and refactor your repository periodically. You should evaluate your repository interface and implementation against your domain model and business logic, and check if they are still aligned and consistent. You should also seek feedback and suggestions from your peers and stakeholders, and learn from their experiences and perspectives. By reviewing and refactoring your repository, you can keep it up to date and relevant, and avoid technical debt or legacy issues.

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Directory

How do you balance performance and abstraction in your repositories?

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1 Understand your domain

2 Choose the right data access strategy

3 Optimize your queries

4 Test and measure your performance

5 Apply the principle of least astonishment

6 Review and refactor your repository

Domain-Driven Design (DDD)

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