- 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
All rows in our database need unique identifiers, typically a sequence of numbers. Alternatively, we can use Universally Unique Identifiers (UUID). In this article, we explore the pros and cons of UUIDs and show how to implement them in a project that uses NestJS, PostgreSQL, and the Drizzle ORM.
Introducing UUIDs
At this point, we’re used to the decimal numeral system, which uses ten symbols (0-9) for values. However, there are alternatives, such as the binary system, which uses just two symbols (0 and 1).
Hexadecimal system
The hexadecimal system uses sixteen symbols ranging from 0 to 9 and from A to F, which is good for representing big numbers. Because of that, UUIDs are hexadecimal numbers that can contain a value that’s over 340 undecillion. One undecillion is a number equal to 1, followed by 36 zeroes.
Thanks to the hexadecimal system, we can shorten the way we write 340 undecillion from 340,000,000,000,000,000,000,000,000,000,000 to 0xFFC99E3C66FD68D2206F414000000000.
We often prefix the hexadecimal numbers with 0x to indicate they follow the hexadecimal system.
To make UUIDs easier to use, we store them with dashes that divide the UUID into five groups, such as ffc99e3c-66fd-68d2-206f-414000000000.
In the hexidecimal system, both uppercase and lowercase characters are valid. They represent the same values, but UUIDs usually use lowercase.
UUIDs can be considered globally unique
There is more than one way to generate a UUID. However, the most common specification is version 4, which generates IDs with pseudo-random numbers.
Most systems generate pseudo-random numbers rather than truly random ones. Computers are deterministic, meaning their operations foillow specific, predictable algorithms.
Generating the same UUID more than once is possible, but the chances are very low. If we generate 103 trillion v4 UUIDs, the chance we create a duplicate is around one in a billion, thanks to a massive number of possible values. This makes it good enough to be considered unique by most applications.
Pros of UUIDs
We probably won’t find a duplicate UUID across multiple tables, databases, or systems. This allows us to merge the data from multiple sources without worrying about colliding IDs. Also, various distributed systems can generate UUIDs independently without running into duplicates.
Debugging and tracing can be more straightforward since UUIDs are unique across all systems. When we see a certain UUID in our logs, we can find the related database row even if we don’t know which table it came from.
When we create a regular sequential ID, we reveal the current number of records. Since UUIDs are random, they don’t have this flaw. This makes it virtually impossible for the attacker to guess the ID of a particular record. Relying solely on security by obscurity is not a good idea, but we could consider it a bonus.
Cons of UUIDs
UUIDs can be a bit harder to read because they are longer and random, as opposed to IDs generated sequentially.
Also, a single UUID takes 16 bytes and is larger than a traditional ID, which typically takes 4 or 8 bytes and can lead to more storage use. Additionally, creating UUIDs requires more computational resources than generating regular, sequential IDs.
UUIDs with the Drizzle ORM
One way of implementing UUIDs with the Drizzle ORM is to use the uuid library. Thanks to the
database.schema.ts
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import { text, pgTable } from 'drizzle-orm/pg-core'; import { v4 as uuid } from 'uuid'; export const articles = pgTable('articles', { id: text('id') .$defaultFn(() => uuid()) .primaryKey(), title: text('title').notNull(), content: text('content').notNull(), }); export const databaseSchema = { articles, }; |
Thanks to the $defaultFn function, we can set up a dynamic default value for a particular column. By pairing it with the uuid library, we get a new, random UUID every time we insert a row into the database using the Drizzle ORM.
Let’s generate a migration that creates our table.
If you want to know more about migrations with the Drizzle ORM, check out API with NestJS #149. Introduction to the Drizzle ORM with PostgreSQL
1 |
npx drizzle-kit generate --name add-articles-table |
0000_add-articles-table.sql
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CREATE TABLE IF NOT EXISTS "articles" ( "id" text PRIMARY KEY NOT NULL, "title" text NOT NULL, "content" text NOT NULL ); |
The crucial thing to notice is that the database does not generate the UUID values since they are not mentioned in the migration. Instead, we create them using the uuid library.
Generating UUIDs with PostgreSQL
The above approach works fine but has some disadvantages. We might want to create rows outside the Drizzle ORM, for example, using the pgAdmin interface. When this happens, we need to generate the UUID manually.
Alternatively, we can set up PostgreSQL to generate the UUID for us with the gen_random_uuid function built into PostgreSQL.
database.schema.ts
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import { text, pgTable } from 'drizzle-orm/pg-core'; import { sql } from 'drizzle-orm'; export const articles = pgTable('articles', { id: text('id') .default(sql`gen_random_uuid()`) .primaryKey(), title: text('title').notNull(), content: text('content').notNull(), }); export const databaseSchema = { articles, }; |
Now, when we run the migration, we can see that PostgreSQL will provide the default value every time we add a row to our table.
0000_add-articles-table.sql
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CREATE TABLE IF NOT EXISTS "articles" ( "id" text PRIMARY KEY DEFAULT gen_random_uuid() NOT NULL, "title" text NOT NULL, "content" text NOT NULL ); |
To use the gen_random_uuid function in our database, we need the pgcrypto extension. To install it, we need to run a simple SQL query.
1 |
CREATE EXTENSION IF NOT EXISTS "pgcrypto"; |
Thanks to handling the UUIDs at the database level, we ensure consistency even if various applications interact with our database. We also don’t have to provide the ID manually when running raw SQL queries.
Adjusting our NestJS application to use strings
The UUIDs are represented as strings, and we need to take this into account when implementing our controller. Instead of sending numerical values with query params, our users will send IDs as strings.
articles.controller.ts
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import { Body, Controller, Delete, Get, Param, Patch, } from '@nestjs/common'; import { ArticlesService } from './articles.service'; import { UpdateArticleDto } from './dto/update-article.dto'; @Controller('articles') export class ArticlesController { constructor(private readonly articlesService: ArticlesService) {} @Get(':id') getById(@Param('id') id: string) { return this.articlesService.getById(id); } @Patch(':id') update(@Param('id') id: string, @Body() article: UpdateArticleDto) { return this.articlesService.update(id, article); } @Delete(':id') async delete(@Param('id') id: string) { await this.articlesService.delete(id); } // ... } |
Summary
In this article, we learned how Universally Unique Identifiers (UUIDs) work and how they can be an alternative to typical numerical sequences. We explored various ways to generate them through examples in a NestJS application that uses the Drizzle ORM and PostgreSQL. Thanks to learning both the advantages and disadvantages of UUIDs, we now know when it makes sense to implement them in our project.