- 1. API with NestJS #1. Controllers, routing and the module structure
- 2. API with NestJS #2. Setting up a PostgreSQL database with TypeORM
- 3. API with NestJS #3. Authenticating users with bcrypt, Passport, JWT, and cookies
- 4. API with NestJS #4. Error handling and data validation
- 5. API with NestJS #5. Serializing the response with interceptors
- 6. API with NestJS #6. Looking into dependency injection and modules
- 7. API with NestJS #7. Creating relationships with Postgres and TypeORM
- 8. API with NestJS #8. Writing unit tests
- 9. API with NestJS #9. Testing services and controllers with integration tests
- 10. API with NestJS #10. Uploading public files to Amazon S3
- 11. API with NestJS #11. Managing private files with Amazon S3
- 12. API with NestJS #12. Introduction to Elasticsearch
- 13. API with NestJS #13. Implementing refresh tokens using JWT
- 14. API with NestJS #14. Improving performance of our Postgres database with indexes
- 15. API with NestJS #15. Defining transactions with PostgreSQL and TypeORM
- 16. API with NestJS #16. Using the array data type with PostgreSQL and TypeORM
- 17. API with NestJS #17. Offset and keyset pagination with PostgreSQL and TypeORM
- 18. API with NestJS #18. Exploring the idea of microservices
- 19. API with NestJS #19. Using RabbitMQ to communicate with microservices
- 20. API with NestJS #20. Communicating with microservices using the gRPC framework
- 21. API with NestJS #21. An introduction to CQRS
- 22. API with NestJS #22. Storing JSON with PostgreSQL and TypeORM
- 23. API with NestJS #23. Implementing in-memory cache to increase the performance
- 24. API with NestJS #24. Cache with Redis. Running the app in a Node.js cluster
- 25. API with NestJS #25. Sending scheduled emails with cron and Nodemailer
- 26. API with NestJS #26. Real-time chat with WebSockets
- 27. API with NestJS #27. Introduction to GraphQL. Queries, mutations, and authentication
- 28. API with NestJS #28. Dealing in the N + 1 problem in GraphQL
- 29. API with NestJS #29. Real-time updates with GraphQL subscriptions
- 30. API with NestJS #30. Scalar types in GraphQL
- 31. API with NestJS #31. Two-factor authentication
- 32. API with NestJS #32. Introduction to Prisma with PostgreSQL
- 33. API with NestJS #33. Managing PostgreSQL relationships with Prisma
- 34. API with NestJS #34. Handling CPU-intensive tasks with queues
- 35. API with NestJS #35. Using server-side sessions instead of JSON Web Tokens
- 36. API with NestJS #36. Introduction to Stripe with React
- 37. API with NestJS #37. Using Stripe to save credit cards for future use
- 38. API with NestJS #38. Setting up recurring payments via subscriptions with Stripe
- 39. API with NestJS #39. Reacting to Stripe events with webhooks
- 40. API with NestJS #40. Confirming the email address
- 41. API with NestJS #41. Verifying phone numbers and sending SMS messages with Twilio
- 42. API with NestJS #42. Authenticating users with Google
- 43. API with NestJS #43. Introduction to MongoDB
- 44. API with NestJS #44. Implementing relationships with MongoDB
- 45. API with NestJS #45. Virtual properties with MongoDB and Mongoose
- 46. API with NestJS #46. Managing transactions with MongoDB and Mongoose
- 47. API with NestJS #47. Implementing pagination with MongoDB and Mongoose
- 48. API with NestJS #48. Definining indexes with MongoDB and Mongoose
- 49. API with NestJS #49. Updating with PUT and PATCH with MongoDB and Mongoose
- 50. API with NestJS #50. Introduction to logging with the built-in logger and TypeORM
- 51. API with NestJS #51. Health checks with Terminus and Datadog
- 52. API with NestJS #52. Generating documentation with Compodoc and JSDoc
- 53. API with NestJS #53. Implementing soft deletes with PostgreSQL and TypeORM
- 54. API with NestJS #54. Storing files inside a PostgreSQL database
- 55. API with NestJS #55. Uploading files to the server
- 56. API with NestJS #56. Authorization with roles and claims
- 57. API with NestJS #57. Composing classes with the mixin pattern
- 58. API with NestJS #58. Using ETag to implement cache and save bandwidth
- 59. API with NestJS #59. Introduction to a monorepo with Lerna and Yarn workspaces
- 60. API with NestJS #60. The OpenAPI specification and Swagger
- 61. API with NestJS #61. Dealing with circular dependencies
- 62. API with NestJS #62. Introduction to MikroORM with PostgreSQL
- 63. API with NestJS #63. Relationships with PostgreSQL and MikroORM
- 64. API with NestJS #64. Transactions with PostgreSQL and MikroORM
- 65. API with NestJS #65. Implementing soft deletes using MikroORM and filters
- 66. API with NestJS #66. Improving PostgreSQL performance with indexes using MikroORM
- 67. API with NestJS #67. Migrating to TypeORM 0.3
- 68. API with NestJS #68. Interacting with the application through REPL
- 69. API with NestJS #69. Database migrations with TypeORM
- 70. API with NestJS #70. Defining dynamic modules
- 71. API with NestJS #71. Introduction to feature flags
- 72. API with NestJS #72. Working with PostgreSQL using raw SQL queries
- 73. API with NestJS #73. One-to-one relationships with raw SQL queries
- 74. API with NestJS #74. Designing many-to-one relationships using raw SQL queries
- 75. API with NestJS #75. Many-to-many relationships using raw SQL queries
- 76. API with NestJS #76. Working with transactions using raw SQL queries
- 77. API with NestJS #77. Offset and keyset pagination with raw SQL queries
- 78. API with NestJS #78. Generating statistics using aggregate functions in raw SQL
- 79. API with NestJS #79. Implementing searching with pattern matching and raw SQL
- 80. API with NestJS #80. Updating entities with PUT and PATCH using raw SQL queries
- 81. API with NestJS #81. Soft deletes with raw SQL queries
- 82. API with NestJS #82. Introduction to indexes with raw SQL queries
- 83. API with NestJS #83. Text search with tsvector and raw SQL
- 84. API with NestJS #84. Implementing filtering using subqueries with raw SQL
- 85. API with NestJS #85. Defining constraints with raw SQL
- 86. API with NestJS #86. Logging with the built-in logger when using raw SQL
- 87. API with NestJS #87. Writing unit tests in a project with raw SQL
- 88. API with NestJS #88. Testing a project with raw SQL using integration tests
- 89. API with NestJS #89. Replacing Express with Fastify
- 90. API with NestJS #90. Using various types of SQL joins
- 91. API with NestJS #91. Dockerizing a NestJS API with Docker Compose
- 92. API with NestJS #92. Increasing the developer experience with Docker Compose
- 93. API with NestJS #93. Deploying a NestJS app with Amazon ECS and RDS
- 94. API with NestJS #94. Deploying multiple instances on AWS with a load balancer
- 95. API with NestJS #95. CI/CD with Amazon ECS and GitHub Actions
- 96. API with NestJS #96. Running unit tests with CI/CD and GitHub Actions
- 97. API with NestJS #97. Introduction to managing logs with Amazon CloudWatch
- 98. API with NestJS #98. Health checks with Terminus and Amazon ECS
- 99. API with NestJS #99. Scaling the number of application instances with Amazon ECS
- 100. API with NestJS #100. The HTTPS protocol with Route 53 and AWS Certificate Manager
- 101. API with NestJS #101. Managing sensitive data using the AWS Secrets Manager
- 102. API with NestJS #102. Writing unit tests with Prisma
- 103. API with NestJS #103. Integration tests with Prisma
- 104. API with NestJS #104. Writing transactions with Prisma
- 105. API with NestJS #105. Implementing soft deletes with Prisma and middleware
- 106. API with NestJS #106. Improving performance through indexes with Prisma
- 107. API with NestJS #107. Offset and keyset pagination with Prisma
- 108. API with NestJS #108. Date and time with Prisma and PostgreSQL
- 109. API with NestJS #109. Arrays with PostgreSQL and Prisma
- 110. API with NestJS #110. Managing JSON data with PostgreSQL and Prisma
- 111. API with NestJS #111. Constraints with PostgreSQL and Prisma
- 112. API with NestJS #112. Serializing the response with Prisma
- 113. API with NestJS #113. Logging with Prisma
- 114. API with NestJS #114. Modifying data using PUT and PATCH methods with Prisma
- 115. API with NestJS #115. Database migrations with Prisma
- 116. API with NestJS #116. REST API versioning
- 117. API with NestJS #117. CORS – Cross-Origin Resource Sharing
- 118. API with NestJS #118. Uploading and streaming videos
- 119. API with NestJS #119. Type-safe SQL queries with Kysely and PostgreSQL
- 120. API with NestJS #120. One-to-one relationships with the Kysely query builder
- 121. API with NestJS #121. Many-to-one relationships with PostgreSQL and Kysely
- 122. API with NestJS #122. Many-to-many relationships with Kysely and PostgreSQL
- 123. API with NestJS #123. SQL transactions with Kysely
- 124. API with NestJS #124. Handling SQL constraints with Kysely
- 125. API with NestJS #125. Offset and keyset pagination with Kysely
- 126. API with NestJS #126. Improving the database performance with indexes and Kysely
- 127. API with NestJS #127. Arrays with PostgreSQL and Kysely
- 128. API with NestJS #128. Managing JSON data with PostgreSQL and Kysely
- 129. API with NestJS #129. Implementing soft deletes with SQL and Kysely
- 130. API with NestJS #130. Avoiding storing sensitive information in API logs
- 131. API with NestJS #131. Unit tests with PostgreSQL and Kysely
- 132. API with NestJS #132. Handling date and time in PostgreSQL with Kysely
- 133. API with NestJS #133. Introducing database normalization with PostgreSQL and Prisma
- 134. API with NestJS #134. Aggregating statistics with PostgreSQL and Prisma
- 135. API with NestJS #135. Referential actions and foreign keys in PostgreSQL with Prisma
- 136. API with NestJS #136. Raw SQL queries with Prisma and PostgreSQL range types
- 137. API with NestJS #137. Recursive relationships with Prisma and PostgreSQL
- 138. API with NestJS #138. Filtering records with Prisma
- 139. API with NestJS #139. Using UUID as primary keys with Prisma and PostgreSQL
- 140. API with NestJS #140. Using multiple PostgreSQL schemas with Prisma
- 141. API with NestJS #141. Getting distinct records with Prisma and PostgreSQL
- 142. API with NestJS #142. A video chat with WebRTC and React
- 143. API with NestJS #143. Optimizing queries with views using PostgreSQL and Kysely
- 144. API with NestJS #144. Creating CLI applications with the Nest Commander
- 145. API with NestJS #145. Securing applications with Helmet
- 146. API with NestJS #146. Polymorphic associations with PostgreSQL and Prisma
- 147. API with NestJS #147. The data types to store money with PostgreSQL and Prisma
- 148. API with NestJS #148. Understanding the injection scopes
- 149. API with NestJS #149. Introduction to the Drizzle ORM with PostgreSQL
- 150. API with NestJS #150. One-to-one relationships with the Drizzle ORM
- 151. API with NestJS #151. Implementing many-to-one relationships with Drizzle ORM
- 152. API with NestJS #152. SQL constraints with the Drizzle ORM
- 153. API with NestJS #153. SQL transactions with the Drizzle ORM
- 154. API with NestJS #154. Many-to-many relationships with Drizzle ORM and PostgreSQL
- 155. API with NestJS #155. Offset and keyset pagination with the Drizzle ORM
- 156. API with NestJS #156. Arrays with PostgreSQL and the Drizzle ORM
- 157. API with NestJS #157. Handling JSON data with PostgreSQL and the Drizzle ORM
- 158. API with NestJS #158. Soft deletes with the Drizzle ORM
- 159. API with NestJS #159. Date and time with PostgreSQL and the Drizzle ORM
- 160. API with NestJS #160. Using views with the Drizzle ORM and PostgreSQL
- 161. API with NestJS #161. Generated columns with the Drizzle ORM and PostgreSQL
- 162. API with NestJS #162. Identity columns with the Drizzle ORM and PostgreSQL
- 163. API with NestJS #163. Full-text search with the Drizzle ORM and PostgreSQL
- 164. API with NestJS #164. Improving the performance with indexes using Drizzle ORM
- 165. API with NestJS #165. Time intervals with the Drizzle ORM and PostgreSQL
- 166. API with NestJS #166. Logging with the Drizzle ORM
- 167. API with NestJS #167. Unit tests with the Drizzle ORM
- 168. API with NestJS #168. Integration tests with the Drizzle ORM
- 169. API with NestJS #169. Unique IDs with UUIDs using Drizzle ORM and PostgreSQL
- 170. API with NestJS #170. Polymorphic associations with PostgreSQL and Drizzle ORM
- 171. API with NestJS #171. Recursive relationships with Drizzle ORM and PostgreSQL
- 172. API with NestJS #172. Database normalization with Drizzle ORM and PostgreSQL
- 173. API with NestJS #173. Storing money with Drizzle ORM and PostgreSQL
- 174. API with NestJS #174. Multiple PostgreSQL schemas with Drizzle ORM
- 175. API with NestJS #175. PUT and PATCH requests with PostgreSQL and Drizzle ORM
- 176. API with NestJS #176. Database migrations with the Drizzle ORM
- 177. API with NestJS #177. Response serialization with the Drizzle ORM
So far, in this series, we’ve focused on working with SQL and the Postgres database. While PostgreSQL is an excellent choice, it is worth checking out the alternatives. In this article, we learn about how MongoDB works and how it differs from SQL databases. We also create a simple application with MongoDB and NestJS.
You can find the source code from the below article in this repository.
MongoDB vs. SQL Databases
The design principles of MongoDB differ quite a bit from traditional SQL databases. Instead of representing data with tables and rows, MongoDB stores it as JSON-like documents. Therefore, it is relatively easy to grasp for developers familiar with JavaScript.
Documents in MongoDB consist of key and value pairs. The significant aspect of them is that the keys can differ across documents in a given collection. This is a big difference between MongoDB and SQL databases. It makes MongoDB a lot more flexible and less structured. Therefore, it can be perceived either as an advantage or a drawback.
Advantages and drawbacks of MongoDB
Since MongoDB and SQL databases differ so much, choosing the right tool for a given job is crucial. Since NoSQL databases put fewer restrictions on the data, it might be a good choice for an application evolving quickly. We still might need to update our data as our schema changes.
For example, we might want to add a new property containing the user’s avatar URL. When it happens, we still should deal with documents not containing our new property. We can do that by writing a script that puts a default value for old documents. Alternatively, we can assume that this field can be missing and handle it differently on the application level.
On the contrary, adding a new property to an existing SQL database requires writing a migration that explicitly handles the new property. This might seem like a bit of a chore in a lot of cases. However, with MongoDB, it is not required. This might make the work easier and faster, but we need to watch out and not lose the integrity of our data.
If you want to know more about SQL migrations, check out The basics of migrations using TypeORM and Postgres
SQL databases such as Postgres keep the data in tables consisting of columns and rows. A big part of the design process is defining relationships between the above tables. For example, a user can be an author of an article. On the other hand, MongoDB is a non-relational database. Therefore, while we can mimic SQL-style relationships with MongoDB, they will not be as efficient and foolproof.
Using MongoDB with NestJS
So far, in this series, we’ve used Docker to set up the architecture for our project. We can easily achieve that with MongoDB also.
docker-compose.yml
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version: "3" services: mongo: image: mongo:latest environment: MONGO_INITDB_ROOT_USERNAME: ${MONGO_USERNAME} MONGO_INITDB_ROOT_PASSWORD: ${MONGO_PASSWORD} MONGO_INITDB_DATABASE: ${MONGO_DATABASE} ports: - '27017:27017' |
Above, you can see that we refer to a few variables. Let’s put them into our .env file:
.env
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MONGO_USERNAME=admin MONGO_PASSWORD=admin MONGO_DATABASE=nestjs MONGO_HOST=localhost:27017 |
In the previous parts of this series, we’ve used TypeORM to connect to our PostgreSQL database and manage our data. For MongoDB, the most popular library is Mongoose.
1 |
npm install --save @nestjs/mongoose mongoose |
Let’s use Mongoose to connect to our database. To do that, we need to define a URI connection string:
app.module.ts
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import { Module } from '@nestjs/common'; import { MongooseModule } from '@nestjs/mongoose'; import { ConfigModule, ConfigService } from '@nestjs/config'; import PostsModule from './posts/posts.module'; import * as Joi from '@hapi/joi'; @Module({ imports: [ ConfigModule.forRoot({ validationSchema: Joi.object({ MONGO_USERNAME: Joi.string().required(), MONGO_PASSWORD: Joi.string().required(), MONGO_DATABASE: Joi.string().required(), MONGO_PATH: Joi.string().required(), }), }), MongooseModule.forRootAsync({ imports: [ConfigModule], useFactory: async (configService: ConfigService) => { const username = configService.get('MONGO_USERNAME'); const password = configService.get('MONGO_PASSWORD'); const database = configService.get('MONGO_DATABASE'); const host = configService.get('MONGO_HOST'); return { uri: `mongodb://${username}:${password}@${host}`, dbName: database, }; }, inject: [ConfigService], }), PostsModule, ], controllers: [], providers: [], }) export class AppModule {} |
Saving and retrieving data
With MongoDB, we operate on documents grouped into collections. To start saving and retrieving data with MongoDB and Mongoose, we first need to define a schema. This might seem surprising at first because MongoDB is considered schemaless. Even though MongoDB is flexible, Mongoose uses schemas to operate on collections and define their shape.
Defining a schema
Every schema maps to a single MongoDB collection. It also defines the shape of the documents within it.
post.schema.ts
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import { Prop, Schema, SchemaFactory } from '@nestjs/mongoose'; import { Document } from 'mongoose'; export type PostDocument = Post & Document; @Schema() export class Post { @Prop() title: string; @Prop() content: string; } export const PostSchema = SchemaFactory.createForClass(Post); |
With the @Schema() decorator, we can mark our class as a schema definition and map it to a MongoDB collection. We use the @Prop() decorator to definite a property of our document. Thanks to TypeScript metadata, the schema types for our properties are automatically inferred.
We will expand on the topic of defining a schema in the upcoming articles.
Working with a model
Mongoose wraps our schemas into models. We can use them to create and read documents. For our service to use the model, we need to add it to our module.
posts.module.ts
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import { Module } from '@nestjs/common'; import { MongooseModule } from '@nestjs/mongoose'; import PostsController from './posts.controller'; import PostsService from './posts.service'; import { Post, PostSchema } from './post.schema'; @Module({ imports: [ MongooseModule.forFeature([{ name: Post.name, schema: PostSchema }]), ], controllers: [PostsController], providers: [PostsService], }) class PostsModule {} export default PostsModule; |
We also need to inject the model into our service:
posts.service.ts
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import { Model } from 'mongoose'; import { Injectable } from '@nestjs/common'; import { InjectModel } from '@nestjs/mongoose'; import { Post, PostDocument } from './post.schema'; @Injectable() class PostsService { constructor(@InjectModel(Post.name) private postModel: Model<PostDocument>) {} } export default PostsService; |
Once we do that, we can start interacting with our collection.
Fetching all entities
The most basic thing we can do is to fetch the list of all of the documents. To do that, we need the find() method:
posts.service.ts
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import { Model } from 'mongoose'; import { Injectable } from '@nestjs/common'; import { InjectModel } from '@nestjs/mongoose'; import { Post, PostDocument } from './post.schema'; @Injectable() class PostsService { constructor(@InjectModel(Post.name) private postModel: Model<PostDocument>) {} async findAll() { return this.postModel.find(); } } |
Fetching a single entity
Every document we create is assigned with a string id. If we want to fetch a single document, we can use the findById method:
posts.service.ts
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import { Model } from 'mongoose'; import { Injectable } from '@nestjs/common'; import { InjectModel } from '@nestjs/mongoose'; import { Post, PostDocument } from './post.schema'; import { NotFoundException } from '@nestjs/common'; @Injectable() class PostsService { constructor(@InjectModel(Post.name) private postModel: Model<PostDocument>) {} async findOne(id: string) { const post = await this.postModel.findById(id); if (!post) { throw new NotFoundException(); } return post; } // ... } |
Creating entities
In the fourth part of this series, we’ve tackled data validation. Let’s create a Data Transfer Object for our entity.
post.dto.ts
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import { IsString, IsNotEmpty } from 'class-validator'; export class PostDto { @IsString() @IsNotEmpty() title: string; @IsString() @IsNotEmpty() content: string; } export default PostDto; |
We can now use it when creating a new instance of our model and saving it.
posts.service.ts
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import { Model } from 'mongoose'; import { Injectable } from '@nestjs/common'; import { InjectModel } from '@nestjs/mongoose'; import { Post, PostDocument } from './post.schema'; import PostDto from './dto/post.dto'; @Injectable() class PostsService { constructor(@InjectModel(Post.name) private postModel: Model<PostDocument>) {} create(postData: PostDto) { const createdPost = new this.postModel(postData); return createdPost.save(); } // ... } |
Updating entities
We might also need to update an entity we’ve already created. To do that, we can use the findByIdAndUpdate method:
posts.service.ts
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import { Model } from 'mongoose'; import { Injectable } from '@nestjs/common'; import { InjectModel } from '@nestjs/mongoose'; import { Post, PostDocument } from './post.schema'; import { NotFoundException } from '@nestjs/common'; import PostDto from './dto/post.dto'; @Injectable() class PostsService { constructor(@InjectModel(Post.name) private postModel: Model<PostDocument>) {} async update(id: string, postData: PostDto) { const post = await this.postModel .findByIdAndUpdate(id, postData) .setOptions({ overwrite: true, new: true }); if (!post) { throw new NotFoundException(); } return post; } // ... } |
Above, a few important things are happening. Thanks to using the new: true parameter, the findByIdAndUpdate method returns an updated version of our entity.
By using overwrite: true, we indicate that we want to replace a whole document instead of performing a partial update. This is what differentiates the PUT and PATCH HTTP methods.
If you want to know more, check out TypeScript Express tutorial #15. Using PUT vs PATCH in MongoDB with Mongoose.
Deleting entities
To delete an existing entity, we need to use the findByIdAndDelete method:
posts.service.ts
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import { Model } from 'mongoose'; import { Injectable } from '@nestjs/common'; import { InjectModel } from '@nestjs/mongoose'; import { Post, PostDocument } from './post.schema'; import { NotFoundException } from '@nestjs/common'; @Injectable() class PostsService { constructor(@InjectModel(Post.name) private postModel: Model<PostDocument>) {} async delete(postId: string) { const result = await this.postModel.findByIdAndDelete(postId); if (!result) { throw new NotFoundException(); } } // ... } |
Defining a controller
Once we’ve got our service up and running, we can use it with our controller:
posts.controller.ts
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import { Body, Controller, Delete, Get, Param, Post, Put, } from '@nestjs/common'; import PostsService from './posts.service'; import ParamsWithId from '../utils/paramsWithId'; import PostDto from './dto/post.dto'; @Controller('posts') export default class PostsController { constructor(private readonly postsService: PostsService) {} @Get() async getAllPosts() { return this.postsService.findAll(); } @Get(':id') async getPost(@Param() { id }: ParamsWithId) { return this.postsService.findOne(id); } @Post() async createPost(@Body() post: PostDto) { return this.postsService.create(post); } @Delete(':id') async deletePost(@Param() { id }: ParamsWithId) { return this.postsService.delete(id); } @Put(':id') async updatePost(@Param() { id }: ParamsWithId, @Body() post: PostDto) { return this.postsService.update(id, post); } } |
The crucial part above is that we’ve defined the ParamsWithId class. With it, we can validate if the provided string is a valid MongoDB id:
paramsWithId.ts
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import { IsMongoId } from 'class-validator'; class ParamsWithId { @IsMongoId() id: string; } export default ParamsWithId; |
Summary
In this article, we’ve learned the very basics of how to use MongoDB with NestJS. To do that, we’ve created a local MongoDB database using Docker Compose and connected it with NestJS and Mongoose. To better grasp MongoDB, we’ve also compared it to SQL databases such as Postgres. There are still a lot of things to cover when it comes to MongoDB, so stay tuned!
Hi! thanks your efforts to create these very usefull documents!
I wondering in the best way to handling mongo versioning with nest, for instance, the __v property of the schemas.
I mean, I want to apply some upgrade logic for some document and update its version.
I don’t know if you have some code example or overview for handling this.
Thanks you so much.