When working with APIs that return large datasets, it’s essential to provide mechanisms like pagination, filtering, and query optimization. These strategies not only enhance user experience but also help improve application performance and reduce server load.

In this module, you’ll learn how to implement efficient pagination, flexible filtering, and optimized queries in NestJS, particularly when using TypeORM.

Table of Contents

1. Why Pagination and Filtering Matter
2. Implementing Pagination
   • Offset-Based Pagination
   • Cursor-Based Pagination (Brief Intro)
3. Adding Filtering to Endpoints
   • Using DTOs for Filters
4. Query Optimization Techniques
5. Practical Example
6. Best Practices
7. Conclusion

Why Pagination and Filtering Matter

Returning an entire database collection in one request is inefficient and unsustainable for both frontend and backend systems. Pagination and filtering allow clients to fetch data incrementally and refine the results, which:

• Reduces bandwidth usage
• Improves database performance
• Enhances user experience with faster load times

Implementing Pagination

Offset-Based Pagination (Standard)

This is the most common method using skip and take with TypeORM.

DTO for Pagination

// dto/pagination-query.dto.ts
import { Type } from 'class-transformer';
import { IsOptional, IsPositive, Min } from 'class-validator';

export class PaginationQueryDto {
  @IsOptional()
  @Type(() => Number)
  @IsPositive()
  limit?: number;

  @IsOptional()
  @Type(() => Number)
  @Min(0)
  offset?: number;
}

Applying in Service

// user.service.ts
async findAll(paginationQuery: PaginationQueryDto) {
  const { limit, offset } = paginationQuery;
  return this.userRepository.find({
    skip: offset,
    take: limit,
    order: { createdAt: 'DESC' },
  });
}

Cursor-Based Pagination (Brief Intro)

While not covered deeply here, cursor-based pagination is recommended for real-time apps and large datasets where offset becomes inefficient. It involves using unique identifiers (like timestamps or IDs) to fetch the next set of data.

Adding Filtering to Endpoints

You can add flexible filtering using optional query parameters.

Using DTOs for Filters

// dto/filter-query.dto.ts
import { IsOptional, IsEmail } from 'class-validator';

export class FilterQueryDto {
  @IsOptional()
  name?: string;

  @IsOptional()
  @IsEmail()
  email?: string;
}

Apply Filters in Query

async findAll(query: PaginationQueryDto & FilterQueryDto) {
  const { limit, offset, name, email } = query;

  const qb = this.userRepository.createQueryBuilder('user');

  if (name) {
    qb.andWhere('user.name LIKE :name', { name: `%${name}%` });
  }

  if (email) {
    qb.andWhere('user.email = :email', { email });
  }

  return qb.skip(offset).take(limit).orderBy('user.createdAt', 'DESC').getMany();
}

Query Optimization Techniques

To improve database performance, apply the following:

1. Select Only Required Fields

qb.select(['user.id', 'user.name']);

2. Use Joins Only When Necessary

qb.leftJoinAndSelect('user.profile', 'profile'); // only if needed

3. Add Indexes to Frequently Queried Fields

In your entity:

@Index()
@Column()
email: string;

4. Use .getRawMany() if You Don’t Need Entity Transformations

const rawUsers = await qb.getRawMany();

Practical Example: Combined Usage

@Get()
async getUsers(
  @Query() paginationQuery: PaginationQueryDto,
  @Query() filterQuery: FilterQueryDto
) {
  return this.userService.findAll({ ...paginationQuery, ...filterQuery });
}

Best Practices

• Validate and sanitize query parameters using DTOs.
• Cap the limit (e.g., max 100) to prevent large data dumps.
• Paginate all list endpoints for scalability.
• Use indexes and optimize queries with profiling tools (e.g., EXPLAIN).
• For large datasets, prefer cursor-based pagination.

Conclusion

Pagination, filtering, and query optimization are crucial for building scalable APIs in NestJS. With a combination of DTO validation, flexible TypeORM queries, and best practices, you can ensure your endpoints are performant and reliable—regardless of the data volume.

Testing is an essential part of building reliable and maintainable NestJS applications. When working with database-driven services, it’s crucial to validate not just isolated logic (unit testing) but also full application behavior (integration testing).

This comprehensive guide will walk you through:

• Writing unit tests for NestJS services that access the database using mocks
• Writing integration tests using real database connections
• Using @nestjs/testing to test full request-response cycles

Table of Contents

1. Why Test Services with DB Access?
2. Unit Testing: Isolated Service Logic
   • Mocking the Repository
   • Writing Unit Tests with Jest
3. Integration Testing with Real Database
   • Setup Using SQLite (In-Memory)
   • Validating Service with Real DB
4. End-to-End (E2E) Testing with HTTP Requests
5. Best Practices
6. Conclusion

Why Test Services with DB Access?

Testing services that communicate with a database ensures:

• Correct handling of data
• Consistency between business logic and persistence layer
• Fewer runtime bugs
• Confidence when refactoring

Unit Testing: Isolated Service Logic

Unit tests validate small, isolated pieces of functionality using mocked dependencies instead of real ones.

Mocking the Repository

Create a mock version of your TypeORM repository.

// test/mocks/user-repository.mock.ts
export const mockUserRepository = () => ({
  findOne: jest.fn(),
  create: jest.fn(),
  save: jest.fn(),
});

Writing Unit Tests with Jest

// user.service.spec.ts
import { Test, TestingModule } from '@nestjs/testing';
import { UserService } from './user.service';
import { getRepositoryToken } from '@nestjs/typeorm';
import { User } from './user.entity';
import { mockUserRepository } from '../test/mocks/user-repository.mock';

describe('UserService - Unit', () => {
  let service: UserService;
  let repo;

  beforeEach(async () => {
    const module: TestingModule = await Test.createTestingModule({
      providers: [
        UserService,
        {
          provide: getRepositoryToken(User),
          useFactory: mockUserRepository,
        },
      ],
    }).compile();

    service = module.get(UserService);
    repo = module.get(getRepositoryToken(User));
  });

  it('should find user by email', async () => {
    const mockUser = { id: 1, email: '[email protected]' };
    repo.findOne.mockResolvedValue(mockUser);

    const result = await service.findByEmail('[email protected]');
    expect(result).toEqual(mockUser);
  });
});

Integration Testing with Real Database

While unit tests mock everything, integration tests use actual database connections, verifying the real behavior of repositories and services.

Setup Using SQLite (In-Memory)

Use an in-memory SQLite DB to avoid modifying production data and ensure fast test runs.

// user.service.int-spec.ts
import { Test, TestingModule } from '@nestjs/testing';
import { TypeOrmModule } from '@nestjs/typeorm';
import { UserService } from './user.service';
import { User } from './user.entity';

describe('UserService - Integration', () => {
  let service: UserService;

  beforeEach(async () => {
    const module: TestingModule = await Test.createTestingModule({
      imports: [
        TypeOrmModule.forRoot({
          type: 'sqlite',
          database: ':memory:',
          dropSchema: true,
          entities: [User],
          synchronize: true,
        }),
        TypeOrmModule.forFeature([User]),
      ],
      providers: [UserService],
    }).compile();

    service = module.get<UserService>(UserService);
  });

  it('should create and fetch user from real DB', async () => {
    const newUser = await service.createUser({ email: '[email protected]' });
    expect(newUser.id).toBeDefined();

    const fetchedUser = await service.findByEmail('[email protected]');
    expect(fetchedUser.email).toBe('[email protected]');
  });
});

End-to-End (E2E) Testing with HTTP Requests

E2E tests use @nestjs/testing with supertest to simulate real HTTP requests to your application.

app.e2e-spec.ts

import { Test } from '@nestjs/testing';
import { INestApplication } from '@nestjs/common';
import { AppModule } from './../src/app.module';
import * as request from 'supertest';

describe('App (e2e)', () => {
  let app: INestApplication;

  beforeAll(async () => {
    const moduleFixture = await Test.createTestingModule({
      imports: [AppModule],
    }).compile();

    app = moduleFixture.createNestApplication();
    await app.init();
  });

  it('/users (POST)', async () => {
    const res = await request(app.getHttpServer())
      .post('/users')
      .send({ email: '[email protected]' })
      .expect(201);

    expect(res.body.email).toEqual('[email protected]');
  });

  it('/users/:email (GET)', async () => {
    await request(app.getHttpServer())
      .get('/users/[email protected]')
      .expect(200);
  });

  afterAll(async () => {
    await app.close();
  });
});

Note:

• Your controller should handle /users POST and /users/:email GET for this to work.
• Include TypeORM SQLite in AppModule for real DB interaction during E2E tests.

Best Practices

• Use unit tests for fast, logic-specific coverage.
• Use integration tests to verify repository interactions.
• Use E2E tests to validate request-response cycles.
• Clean up test DBs after each run to avoid pollution.
• Keep mocks in a test/mocks/ directory and reuse them across tests.

Conclusion

In this article, we explored both unit and integration testing for services that use database access in NestJS. You learned how to:

• Use mocks for unit testing repository interactions.
• Set up SQLite in-memory DB for lightweight integration tests.
• Use @nestjs/testing and supertest to simulate real HTTP requests in E2E testing.

By combining these techniques, you can build a well-tested, stable, and production-ready NestJS backend.

Database transactions are critical when you need to ensure that a series of operations either all succeed or all fail together. This becomes especially important when handling complex logic such as financial transfers, user registrations involving multiple tables, or updating related records.

In this article, we’ll explore how to implement database transactions in NestJS using TypeORM, including manual and transactional entity manager approaches. We’ll also discuss the benefits and use cases of using transactions in your backend logic.

Table of Contents

1. What is a Database Transaction?
2. Why Use Transactions in NestJS?
3. Using TypeORM’s @Transaction Decorator (Deprecated)
4. Using QueryRunner for Manual Transactions
5. Using DataSource#transaction() Method
6. Best Practices for Transactions
7. Conclusion

What is a Database Transaction?

A database transaction is a sequence of operations performed as a single logical unit of work. These operations either all succeed (commit) or fail (rollback), preserving data integrity.

The four key properties of a transaction (ACID) are:

• Atomicity: All changes succeed or none do.
• Consistency: Data remains valid and consistent.
• Isolation: Transactions do not interfere with each other.
• Durability: Once committed, changes are permanent.

Why Use Transactions in NestJS?

In a NestJS application, transactions are useful when:

• Creating related records in multiple tables.
• Updating and rolling back on failure.
• Preventing partial writes that corrupt data.
• Coordinating multiple repository operations within a single request.

Using TypeORM’s @Transaction Decorator (Deprecated)

TypeORM previously supported the @Transaction() decorator, but it has been deprecated and should be avoided in newer applications. Instead, prefer using QueryRunner or DataSource.transaction().

Using QueryRunner for Manual Transactions

QueryRunner provides fine-grained control over database transactions. You can start a transaction, execute queries, and either commit or rollback manually.

Example: Manual Transaction with QueryRunner

import { Injectable } from '@nestjs/common';
import { DataSource } from 'typeorm';
import { User } from './user.entity';
import { Profile } from './profile.entity';

@Injectable()
export class UserService {
  constructor(private dataSource: DataSource) {}

  async createUserWithProfile(userData: any, profileData: any) {
    const queryRunner = this.dataSource.createQueryRunner();

    await queryRunner.connect();
    await queryRunner.startTransaction();

    try {
      const user = queryRunner.manager.create(User, userData);
      await queryRunner.manager.save(user);

      const profile = queryRunner.manager.create(Profile, {
        ...profileData,
        user,
      });
      await queryRunner.manager.save(profile);

      await queryRunner.commitTransaction();

      return { user, profile };
    } catch (err) {
      await queryRunner.rollbackTransaction();
      throw err;
    } finally {
      await queryRunner.release();
    }
  }
}

Explanation

• We create and connect a QueryRunner.
• Start a transaction using startTransaction().
• Perform operations using queryRunner.manager.
• Commit or rollback depending on whether an error occurs.
• Always release the query runner in finally.

Using DataSource#transaction() Method

The modern and cleaner way to handle transactions is using the DataSource.transaction() method. This method takes care of connection management and error handling internally.

Example: DataSource.transaction() Usage

@Injectable()
export class UserService {
  constructor(private dataSource: DataSource) {}

  async createUserWithProfile(userData: any, profileData: any) {
    return await this.dataSource.transaction(async (manager) => {
      const user = manager.create(User, userData);
      await manager.save(user);

      const profile = manager.create(Profile, {
        ...profileData,
        user,
      });
      await manager.save(profile);

      return { user, profile };
    });
  }
}

Why Use DataSource.transaction()?

• Simplifies boilerplate code.
• Handles rollback automatically on failure.
• Ensures transactional integrity with cleaner syntax.

Best Practices for Transactions

Here are some tips to follow when using transactions in NestJS:

1. Avoid long-running logic inside a transaction — keep it fast.
2. Always release QueryRunner if using it manually.
3. Wrap only critical sections that require atomicity.
4. Use repository methods inside transactions rather than raw queries where possible.
5. Log failures and always handle rollback scenarios.

Conclusion

Database transactions are a vital feature when working with critical data in NestJS applications. With TypeORM’s QueryRunner or DataSource.transaction(), you can implement reliable and consistent transactional logic that maintains data integrity even in complex scenarios.

In this module, you’ve learned the different ways to handle transactions and the best practices for implementing them correctly in NestJS.

In a relational database, schema relationships define how different tables (entities) are connected to each other. Understanding these relationships is crucial when designing a database for a NestJS application. This module will guide you through the process of defining schema relationships using TypeORM and running migrations to update your database schema over time.

We’ll cover the following concepts in this module:

1. One-to-One, One-to-Many, and Many-to-Many Relationships.
2. Using TypeORM to define these relationships in your NestJS entities.
3. Running migrations to keep your database schema in sync with your codebase.

Table of Contents

1. Introduction to Schema Relationships
2. Defining One-to-One Relationships
3. Defining One-to-Many Relationships
4. Defining Many-to-Many Relationships
5. Using TypeORM Migrations
6. Running Migrations in NestJS
7. Conclusion

Introduction to Schema Relationships

Schema relationships in relational databases are essential for modeling the real-world connections between different entities. Some of the common types of relationships are:

• One-to-One: A relationship where each record in one table is related to only one record in another table.
• One-to-Many: A relationship where a record in one table can be related to multiple records in another table.
• Many-to-Many: A relationship where multiple records in one table can be related to multiple records in another table.

In NestJS, TypeORM makes it easy to define and manage these relationships through decorators in your entity classes.

Defining One-to-One Relationships

A One-to-One relationship occurs when a single record in one table is associated with only one record in another table. For example, a User might have one Profile.

Example: Defining One-to-One Relationship

// src/user/user.entity.ts
import { Entity, PrimaryGeneratedColumn, Column, OneToOne, JoinColumn } from 'typeorm';
import { Profile } from '../profile/profile.entity';

@Entity()
export class User {
  @PrimaryGeneratedColumn()
  id: number;

  @Column()
  name: string;

  @OneToOne(() => Profile)
  @JoinColumn()
  profile: Profile;
}

// src/profile/profile.entity.ts
import { Entity, PrimaryGeneratedColumn, Column } from 'typeorm';

@Entity()
export class Profile {
  @PrimaryGeneratedColumn()
  id: number;

  @Column()
  bio: string;
}

In this example:

• @OneToOne() establishes the one-to-one relationship between User and Profile.
• @JoinColumn() specifies that the User entity will hold the foreign key to the Profile entity.

Defining One-to-Many Relationships

A One-to-Many relationship happens when one record in a table is related to multiple records in another table. For instance, a Category can have multiple Products.

Example: Defining One-to-Many Relationship

// src/category/category.entity.ts
import { Entity, PrimaryGeneratedColumn, Column, OneToMany } from 'typeorm';
import { Product } from '../product/product.entity';

@Entity()
export class Category {
  @PrimaryGeneratedColumn()
  id: number;

  @Column()
  name: string;

  @OneToMany(() => Product, (product) => product.category)
  products: Product[];
}

// src/product/product.entity.ts
import { Entity, PrimaryGeneratedColumn, Column, ManyToOne } from 'typeorm';
import { Category } from '../category/category.entity';

@Entity()
export class Product {
  @PrimaryGeneratedColumn()
  id: number;

  @Column()
  name: string;

  @ManyToOne(() => Category, (category) => category.products)
  category: Category;
}

In this example:

• @OneToMany() defines the one-to-many relationship from Category to Product.
• @ManyToOne() establishes the inverse relationship in the Product entity.

Defining Many-to-Many Relationships

A Many-to-Many relationship occurs when multiple records in one table are related to multiple records in another table. For example, an Author can write multiple Books, and a Book can be written by multiple Authors.

Example: Defining Many-to-Many Relationship

// src/author/author.entity.ts
import { Entity, PrimaryGeneratedColumn, Column, ManyToMany, JoinTable } from 'typeorm';
import { Book } from '../book/book.entity';

@Entity()
export class Author {
  @PrimaryGeneratedColumn()
  id: number;

  @Column()
  name: string;

  @ManyToMany(() => Book)
  @JoinTable()
  books: Book[];
}

// src/book/book.entity.ts
import { Entity, PrimaryGeneratedColumn, Column, ManyToMany } from 'typeorm';
import { Author } from '../author/author.entity';

@Entity()
export class Book {
  @PrimaryGeneratedColumn()
  id: number;

  @Column()
  title: string;

  @ManyToMany(() => Author, (author) => author.books)
  authors: Author[];
}

In this example:

• @ManyToMany() defines the many-to-many relationship between Author and Book.
• @JoinTable() is used on one side of the relationship to specify the junction table that will manage the many-to-many relationship.

Using TypeORM Migrations

A migration in TypeORM allows you to manage and apply schema changes to your database. Migrations are helpful when you need to track changes to your database schema over time and keep your production and development environments in sync.

Creating a Migration

To create a migration, you can use the following command:

npx typeorm migration:generate -n MigrationName

This will create a migration file in the src/migration folder with the necessary SQL to update the database schema based on the changes in your entities.

Example: Migration for Schema Changes

Suppose you add a new column to an existing entity. You would create a migration as shown above, which might look something like this:

// src/migration/1618560247852-AddNewColumnToUser.ts
import {MigrationInterface, QueryRunner} from "typeorm";

export class AddNewColumnToUser1618560247852 implements MigrationInterface {
    public async up(queryRunner: QueryRunner): Promise<void> {
        await queryRunner.addColumn("user", new TableColumn({
            name: "newColumn",
            type: "varchar",
            isNullable: true,
        }));
    }

    public async down(queryRunner: QueryRunner): Promise<void> {
        await queryRunner.dropColumn("user", "newColumn");
    }
}

In the up() method, you define the changes to apply to the schema, and in the down() method, you define how to revert those changes.

Running Migrations in NestJS

After creating your migration, you need to run it to apply the changes to the database. Use the following command:

npx typeorm migration:run

This will execute the migrations and update your database schema.

To revert a migration, you can use:

npx typeorm migration:revert

Conclusion

In this module, we learned how to define schema relationships in NestJS using TypeORM. We explored One-to-One, One-to-Many, and Many-to-Many relationships, which allow you to model complex data structures in your database. Additionally, we covered how to create and run migrations to keep your database schema in sync with the application code.

By using schema relationships and migrations, you can maintain a well-structured and consistent database while ensuring that your application’s data model evolves in a controlled and predictable manner.

The Repository Pattern is a structural pattern that provides an abstraction layer between the data access logic and business logic in your application. By using repositories, you can decouple your database queries from the rest of your application and encapsulate the logic for querying and manipulating data. In NestJS, the Repository Pattern works seamlessly with ORMs like TypeORM and Prisma, offering a clean and maintainable approach to managing database operations.

In this module, we’ll dive into the Repository Pattern, explain its benefits, and show you how to use it effectively in NestJS. We will also cover how to work with Entities in NestJS to model your database tables and interact with them using repositories.

Table of Contents

1. Introduction to Repository Pattern
2. Working with Entities in NestJS
3. Implementing the Repository Pattern in NestJS
4. Example: Creating and Retrieving Data with Repository Pattern
5. Benefits of the Repository Pattern
6. Conclusion

Introduction to Repository Pattern

The Repository Pattern is used to isolate the domain layer from the persistence layer (e.g., database). This separation helps to keep your business logic clean and focused, without mixing it with database-specific operations.

In the Repository Pattern:

• The repository serves as an intermediary between the business logic and the data storage (usually a database).
• It encapsulates the logic needed to retrieve and store entities, abstracting away the details of the data source.
• This pattern is especially useful when your application requires complex queries or if you are working with multiple data sources.

By using this pattern, you can easily switch your database provider (e.g., from PostgreSQL to MongoDB) or modify your query logic without affecting the rest of your application.

Working with Entities in NestJS

In NestJS, entities are used to define the structure of database tables. They represent the schema of your database, with each entity corresponding to a table.

To define an entity in NestJS using TypeORM, you use decorators like @Entity(), @Column(), and @PrimaryGeneratedColumn(). These decorators define the properties of the entity and map them to the database columns.

Example: Defining an Entity

Let’s say we want to create a User entity. Here’s how you would define it in NestJS using TypeORM:

// src/user/user.entity.ts
import { Entity, PrimaryGeneratedColumn, Column } from 'typeorm';

@Entity()
export class User {
  @PrimaryGeneratedColumn()
  id: number;

  @Column()
  name: string;

  @Column()
  email: string;
}

In this example:

• @Entity() marks the class as an entity, representing a table in the database.
• @PrimaryGeneratedColumn() specifies that id will be the primary key and automatically generated.
• @Column() is used to define regular columns in the table, like name and email.

Once the entity is defined, you can use it to create and query data from the database.

Implementing the Repository Pattern in NestJS

To implement the Repository Pattern in NestJS, we typically create a repository class that abstracts the logic for interacting with the database. Repositories are typically injected into services, where business logic is implemented.

In TypeORM, repositories can be accessed using @InjectRepository() and used to perform operations on the database.

Step 1: Create a Repository Class

A repository class serves as a wrapper around TypeORM’s repository, providing methods to interact with the database. Here’s an example of a repository class for managing User entities.

// src/user/user.repository.ts
import { EntityRepository, Repository } from 'typeorm';
import { User } from './user.entity';

@EntityRepository(User)
export class UserRepository extends Repository<User> {
  async findByEmail(email: string): Promise<User | undefined> {
    return this.findOne({ where: { email } });
  }
}

In this example:

• @EntityRepository(User) tells TypeORM that this repository is for the User entity.
• UserRepository extends Repository<User>, which provides basic CRUD operations.
• We added a custom method findByEmail(), which allows us to query users by their email.

Step 2: Inject the Repository into a Service

Now, we’ll inject the repository into a service and use it to interact with the database.

// src/user/user.service.ts
import { Injectable } from '@nestjs/common';
import { InjectRepository } from '@nestjs/typeorm';
import { User } from './user.entity';
import { UserRepository } from './user.repository';

@Injectable()
export class UserService {
  constructor(
    @InjectRepository(User)
    private readonly userRepository: UserRepository,
  ) {}

  async createUser(name: string, email: string): Promise<User> {
    const user = this.userRepository.create({ name, email });
    return this.userRepository.save(user);
  }

  async getUserByEmail(email: string): Promise<User | undefined> {
    return this.userRepository.findByEmail(email);
  }

  async getAllUsers(): Promise<User[]> {
    return this.userRepository.find();
  }
}

In this example:

• The UserRepository is injected into the UserService using @InjectRepository().
• We use the repository’s methods to perform database operations such as creating a user and retrieving users by email.

Example: Creating and Retrieving Data with Repository Pattern

Let’s walk through an example where we create a user and retrieve them by email.

Step 1: Create a User

You can call the createUser method from the service to create a new user.

// src/user/user.controller.ts
import { Controller, Post, Body } from '@nestjs/common';
import { UserService } from './user.service';

@Controller('users')
export class UserController {
  constructor(private readonly userService: UserService) {}

  @Post()
  async createUser(@Body() body: { name: string; email: string }) {
    return this.userService.createUser(body.name, body.email);
  }
}

Step 2: Get User by Email

You can call the getUserByEmail method from the service to retrieve a user by their email.

// src/user/user.controller.ts
import { Controller, Get, Param } from '@nestjs/common';
import { UserService } from './user.service';

@Controller('users')
export class UserController {
  constructor(private readonly userService: UserService) {}

  @Get(':email')
  async getUser(@Param('email') email: string) {
    return this.userService.getUserByEmail(email);
  }
}

Benefits of the Repository Pattern

Using the Repository Pattern in your application offers several benefits:

1. Separation of Concerns: The repository abstracts away the data access logic, allowing you to focus on business logic in your services.
2. Maintainability: By encapsulating data operations in repositories, it becomes easier to modify or replace data access logic without affecting the rest of the application.
3. Testability: With the repository pattern, it’s easier to mock or stub data access layers during unit testing, as your services do not directly interact with the database.
4. Consistency: Using repositories ensures consistent methods for interacting with the database throughout the application.

Conclusion

In this module, we explored the Repository Pattern and how it can be implemented in NestJS using TypeORM. We covered the process of defining entities, creating repository classes, and injecting repositories into services to manage database operations.

The Repository Pattern helps to improve maintainability, testability, and separation of concerns in your NestJS application. By using repositories and entities, you can effectively manage data and keep your application’s business logic clean and focused.