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Best Practices
Learn the best practices for using Monarch ORM effectively, including optimization techniques, security considerations, and recommended patterns. Following these guidelines can help you write cleaner, more maintainable, and performant code.
1. Schema Design
- Define schemas carefully: Spend time designing your schemas to accurately represent your data models. Consider relationships between entities and how you will query your data.
- Use appropriate types: Select the most appropriate data types for each field to ensure data integrity and type safety. Leverage features like
string().lowercase()
andnumber().default()
to enforce data constraints directly in your schema. - Utilize schema modifiers: Use
nullable()
,optional()
, anddefault()
to clearly define field behavior and reduce boilerplate code in your application logic. - Consider Indexes early: Plan your indexes while defining the schema and leverage compound indexes effectively.
2. Data Validation
- Rely on schema validation: Monarch ORM enforces your schema, reducing the risk of runtime errors caused by invalid data. Make use of this as your first line of defense.
- Leverage transformations: Use
.lowercase()
,.uppercase()
,.trim()
, and other transformation methods to automatically sanitize data before it is stored in the database.
3. Querying for data
- Use projections (
select
andomit
): Retrieve only the fields you need to minimize data transfer and improve query performance. - Paginate large result sets: Implement pagination to avoid loading excessive amounts of data into memory.
- Leverage Aggregation Framework when needed: Use MongoDB's aggregation framework for complex data transformations and calculations.
- Consider Indexes: Ensure you have appropriate indexes for frequent queries
4. Relationships and Population
- Define relationships carefully: Clearly define relationships between schemas using
one
,many
, andref
. - Use Population Strategically: Population can be expensive. Only populate relationships when necessary.
- Use Population Options: Use population options (
select
,omit
,limit
,skip
,sort
) to optimize the population process.
- Cache Frequent Data: For very common related document values, consider caching the results of population to minimize database load.
5. Performance Optimization
- Use indexes: Properly configured indexes are crucial for query performance.
- Profile your queries: Use MongoDB's profiling tools to identify slow queries and optimize them.
- Monitor database performance: Regularly monitor your MongoDB server to ensure it is running smoothly and to identify any performance bottlenecks.
- Leverage connection pooling: Monarch ORM relies on the underlying MongoDB driver for connection pooling. Ensure that your driver is configured correctly to reuse connections efficiently.
- Use BSON options: Set the correct
BSONOptions
for high throughput or low latency for large or sensitive requests.
6. Error Handling
- Handle exceptions gracefully: Wrap your database operations in
try...catch
blocks to handle potential errors. - Use logging: Log errors and warnings to help you diagnose and resolve issues.
- Implement retry logic: For transient errors, consider implementing retry logic to improve resilience.
7. Code Organization and Maintainability
- Separate schema definitions: Define your schemas in separate files for better organization.
- Use dependency injection: Inject your database client and collections into your application components to improve testability and flexibility.
- Follow a consistent coding style: Adhere to a consistent coding style throughout your project to improve readability and maintainability.
- Use a Linter and Formatter: Use a style guide to improve readability. Monarch orm ships with biomejs for code formatting.
- Write tests: Thoroughly test your data access code to ensure it is working correctly.
Example Project Structure
By following these best practices, you can build robust, scalable, and maintainable applications with Monarch ORM and MongoDB.