- 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
- 178. API with NestJS #178. Storing files inside of a PostgreSQL database with Drizzle
- 179. API with NestJS #179. Pattern matching search with Drizzle ORM and PostgreSQL
- 180. API with NestJS #180. Organizing Drizzle ORM schema with PostgreSQL
In PostgreSQL, schemas act as namespaces within the database and are containers for objects such as tables and indexes. In this article, we explain how they work and what are their benefits. We also provide examples of how to use them with Prisma.
The public schema
PostgreSQL creates a schema called public out of the box for every new database. Let’s say we have the following Article model.
schema.prisma
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model Article { id Int @id @default(autoincrement()) title String content String } |
When we generate a migration, we can see that it does not mention any schemas at all.
If you want to know more about migrations with Prisma, check out API with NestJS #115. Database migrations with Prisma
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npx prisma migrate dev --name create-article-table |
migration.sql
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-- CreateTable CREATE TABLE "Article" ( "id" SERIAL NOT NULL, "title" TEXT NOT NULL, "content" TEXT NOT NULL, CONSTRAINT "Article_pkey" PRIMARY KEY ("id") ); |
This is because, by default, when we create a table without specifying the schema, PostgreSQL attaches it to the public schema.
Similarly, when we make a SQL query and don’t specify the schema, PostgreSQL assumes that we mean to use the public schema.
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SELECT * FROM "Article"; |
Determining the schema to use
This is controlled through the search_path variable built into PostgreSQL. It contains the order of schemas PostgreSQL needs to look for when we make a query without specifying the schema explicitly.
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SHOW search_path; |
By default, it contains "$user", public. The "$user" refers to the current user’s name that we can check through the current_user variable.
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SELECT current_user; |
Therefore, "$user", public in our case means that PostgreSQL first tries to look for the "Article" table in the admin schema, then in the public schema.
By default, the admin schema does not exist. If that’s the case, PostgreSQL ignores it.
We could change the default schema by modifying the search_path variable.
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SET search_path TO another_schema_name; |
Fortunately, we can quickly go back to the default value.
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SET search_path TO DEFAULT; |
If we want to be explicit in our query, we can prepend the table’s name with the schema we want to use.
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SELECT * FROM public."Article"; |
Creating new schemas
We need to enable the multiSchema preview feature to start using additional schemas with Prisma.
schema.prisma
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generator client { provider = "prisma-client-js" previewFeatures = ["multiSchema"] } |
We also need to list the schemas we want to use.
schema.prisma
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datasource db { provider = "postgresql" url = env("DATABASE_URL") schemas = ["user_data"] } |
Now, we need to use the @@schema attribute to specify which schema we want to use with a particular model in our database.
schema.prisma
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model Address { id Int @id @default(autoincrement()) street String city String country String user User? @@schema("user_data") } model User { id Int @id @default(autoincrement()) email String @unique name String password String address Address? @relation(fields: [addressId], references: [id]) addressId Int? @unique @@schema("user_data") } |
The above code uses relationships. If you want to know more, check out API with NestJS #33. Managing PostgreSQL relationships with Prisma
However, when we try to run a migration, we might encounter a problem.
1 |
npx prisma migrate dev --name add-user-data |
1234567891011 Error: Prisma schema validation - (validate wasm)Error code: P1012error: Error validating model "Article": This model is missing an `@@schema` attribute.--> schema.prisma:12|11 |12 | model Article {13 | id Int @id @default(autoincrement())14 | title String15 | content String16 | }
This is because when we start using multiple PostgreSQL schemas with Prisma, we need to use the @@schema with every model. Let’s add the public schema to our list of schemas and use it with the Article model.
schema.prisma
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datasource db { provider = "postgresql" url = env("DATABASE_URL") schemas = ["public", "user_data"] } model Article { id Int @id @default(autoincrement()) title String content String @@schema("public") } |
Now, the migration works as expected.
migration.sql
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-- CreateSchema CREATE SCHEMA IF NOT EXISTS "user_data"; -- CreateTable CREATE TABLE "user_data"."Address" ( "id" SERIAL NOT NULL, "street" TEXT NOT NULL, "city" TEXT NOT NULL, "country" TEXT NOT NULL, CONSTRAINT "Address_pkey" PRIMARY KEY ("id") ); -- CreateTable CREATE TABLE "user_data"."User" ( "id" SERIAL NOT NULL, "email" TEXT NOT NULL, "name" TEXT NOT NULL, "password" TEXT NOT NULL, "addressId" INTEGER, CONSTRAINT "User_pkey" PRIMARY KEY ("id") ); -- CreateIndex CREATE UNIQUE INDEX "User_email_key" ON "user_data"."User"("email"); -- CreateIndex CREATE UNIQUE INDEX "User_addressId_key" ON "user_data"."User"("addressId"); -- AddForeignKey ALTER TABLE "user_data"."User" ADD CONSTRAINT "User_addressId_fkey" FOREIGN KEY ("addressId") REFERENCES "user_data"."Address"("id") ON DELETE SET NULL ON UPDATE CASCADE; |
Please notice that the above migration does not interact with the Article table, even though we added the @@schema attribute.
Naming the models
Whenever we interact with our models, we don’t need to provide the name of the schema they come from.
articles.service.ts
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import { Injectable } from '@nestjs/common'; import { PrismaService } from '../database/prisma.service'; @Injectable() export class ArticlesService { constructor(private readonly prismaService: PrismaService) {} getAll() { return this.prismaService.article.findMany(); } // ... } |
While convenient, all our model names must be unique, even if they come from different schemas.
One of the ways to archive some rows from a table is to create a separate table to hold the archived entities. Let’s do that, but create the new table in a separate schema.
migration.sql
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datasource db { provider = "postgresql" url = env("DATABASE_URL") schemas = ["public", "user_data", "archive"] } model Article { id Int @id @default(autoincrement()) title String content String @@schema("public") } model Article { id Int @id @default(autoincrement()) title String content String @@schema("archive") } |
While PostgreSQL allows us to reuse the same table name across various schemas, Prisma won’t allow us to have two models with the same name.
1 |
npx prisma migrate dev --name add-archived-articles |
12345678 Error: Prisma schema validation - (validate wasm)Error code: P1012error: The model "Article" cannot be defined because a model with that name already exists.--> schema.prisma:20|19 |20 | model Article {|
If we want to use the same table name in two different schemas while using Prisma, we need to come up with a different model name and use the @@map attribute to specify the table name.
schema.prisma
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model Article { id Int @id @default(autoincrement()) title String content String @@schema("public") } model ArchivedArticle { id Int @id @default(autoincrement()) title String content String @@schema("archive") @@map("Article") } |
Benefits of using schemas
Using multiple schemas with PostgreSQL offers a few benefits. Organizing our data into schemas can help to organize our data within the same database and make it easier to navigate the database structure. Schemas also give us better control over the access permissions in our database. We can restrict some users from interacting with a particular schema, which can be useful if we have many different users in our database.
Another benefit is that schemas can help us deal with naming conflicts. If different teams work separately on the database, they can use tables or indexes with the same names as long as they use dedicated schemas. Additionally, routine maintenance tasks such as backups can target specific schemas without affecting the entire database.
Summary
Schemas can help us manage our data in a way that increases security, efficiency, and clarity. They can be especially useful in complex or multi-user environments.
To learn how to work with them, we first interacted with our database through raw SQL queries to learn how PostgreSQL works when we don’t specify the schema explicitly. Then, we used Prisma to define additional schemas and assign models to them. Mastering schemas in PostgreSQL can make your database simpler to use and manage, especially if it grows and gets more users and tables.
That’s how I’m building a multi-tenancy app: by using a different schema for each client.