- 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
Saving date and time in our database can be tricky, but it’s crucial to do it correctly. In this article, we address this problem using PostgreSQL and Kysely. We also explore time zones and how to handle them when designing our database.
Dates in PostgreSQL
We can determine how our database handles dates by examining the DateStyle parameter.
By default, DateStyle is set to ISO, MDY. To learn about other options, take a look at the official documentation.
The result of the query above includes two parts:
- the default date and time output,
- instructions on how to understand the input.
By default, PostgreSQL represents dates following the ISO 8601 standard, which means the default display format is YYYY-MM-DD.
The DateStyle parameter also tells us that PostgreSQL interprets given dates as month-day-year (MDY).
Because the input format is set to MDY, PostgreSQL treats the first number as the month and the second as the day. Ignoring this can lead to errors when entering our data.
Date columns built into PostgreSQL
There are various column types to pick from when describing the date and time.
DATE
The most straightforward column type we can choose is DATE.
20231105201749_add_created_at_to_articles.ts
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import { Kysely } from 'kysely'; export async function up(database: Kysely<unknown>): Promise<void> { await database.schema .alterTable('articles') .addColumn('created_at', 'date') .execute(); } export async function down(database: Kysely<unknown>): Promise<void> { await database.schema.alterTable('articles').dropColumn('created_at'); } |
This column allows us to store the date without the time. When we retrieve the data from the database, it is an instance of the Date class.
articlesTable.ts
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import { Generated } from 'kysely'; export interface ArticlesTable { id: Generated<number>; title: string; paragraphs: string[]; author_id: number; created_at?: Date; } |
In the dates retrieved from the database, the time is set to 00:00:00.
articles.repository.ts
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import { Database } from '../database/database'; import { Article } from './article.model'; import { Injectable } from '@nestjs/common'; @Injectable() export class ArticlesRepository { constructor(private readonly database: Database) {} async getById(id: number) { const databaseResponse = await this.database .selectFrom('articles') .where('id', '=', id) .selectAll() .executeTakeFirst(); if (databaseResponse) { console.log(databaseResponse.created_at instanceof Date); // true // Sun Nov 05 2023 00:00:00 GMT+0100 (Central European Standard Time) console.log(databaseResponse.created_at?.toString()); return new Article(databaseResponse); } } // ... } |
TIME
If we want to store the time without the date, we can use the TIME column.
20231105201749_add_created_at_to_articles.ts
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import { Kysely } from 'kysely'; export async function up(database: Kysely<unknown>): Promise<void> { await database.schema .alterTable('articles') .addColumn('created_at', 'time') .execute(); } export async function down(database: Kysely<unknown>): Promise<void> { await database.schema.alterTable('articles').dropColumn('created_at'); } |
When using the TIME column, the retrieved data is a string.
articlesTable.ts
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import { Generated } from 'kysely'; export interface ArticlesTable { id: Generated<number>; title: string; paragraphs: string[]; author_id: number; created_at?: string; } |
We can investigate that in our repository.
articles.repository.ts
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import { Database } from '../database/database'; import { Article } from './article.model'; import { Injectable } from '@nestjs/common'; @Injectable() export class ArticlesRepository { constructor(private readonly database: Database) {} async getById(id: number) { const databaseResponse = await this.database .selectFrom('articles') .where('id', '=', id) .selectAll() .executeTakeFirst(); if (databaseResponse) { console.log(typeof databaseResponse.created_at); // string console.log(databaseResponse.created_at); // 13:15 return new Article(databaseResponse); } } // ... } |
TIMESTAMP
Another important date column is the TIMESTAMP.
20231105201749_add_created_at_to_articles.ts
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import { Kysely } from 'kysely'; export async function up(database: Kysely<unknown>): Promise<void> { await database.schema .alterTable('articles') .addColumn('created_at', 'timestamp') .execute(); } export async function down(database: Kysely<unknown>): Promise<void> { await database.schema.alterTable('articles').dropColumn('created_at'); } |
PostgreSQL stores the timestamp as a numeric value representing a specific moment in time. The way it’s displayed can be influenced by the DateStyle parameter. Since the default is set to ISO, MDY, PostgreSQL displays the date in the ISO format.
When using the TIMESTAMP column, the retrieved data is an instance of the Date class.
articlesTable.ts
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import { Generated } from 'kysely'; export interface ArticlesTable { id: Generated<number>; title: string; paragraphs: string[]; author_id: number; created_at?: Date; } |
The data that comes from the database includes both the date and the time.
articles.repository.ts
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import { Database } from '../database/database'; import { Article } from './article.model'; import { Injectable } from '@nestjs/common'; @Injectable() export class ArticlesRepository { constructor(private readonly database: Database) {} async getById(id: number) { const databaseResponse = await this.database .selectFrom('articles') .where('id', '=', id) .selectAll() .executeTakeFirst(); if (databaseResponse) { console.log(databaseResponse.created_at instanceof Date); // true // Sun Nov 05 2023 15:30:34 GMT+0100 (Central European Standard Time) console.log(databaseResponse.created_at?.toString()); return new Article(databaseResponse); } } // ... } |
Timezones
The Coordinated Universal Time (UTC) is the primary time standard determined by atomic clocks. Timezones are usually defined by the number of hours ahead or behind UTC.
For instance, Eastern Standard Time (EST) can be expressed as UTC -5. So, if the current UTC is 20:00, the time in New York would be 15:00.
Dealing with time zones can be challenging, as they are linked to geography and politics and can be influenced by daylight saving adjustments. This video offers a great overview of various factors to keep in mind.
PostgreSQL didn’t perform any timezone-related conversions when we used the TIME and TIMESTAMP columns in this article. This means that when we input a specific date into our database, it will remain the same, regardless of the timezone we later use to display it.
Both of these types have counterparts that take time zones into account. When we use the TIMESTAMPTZ data type, we can provide the timezone and date. PostgreSQL then converts our input and stores it as UTC.
The official PostgreSQL documentation advises against using the TIMETZ type, which represents time with a timezone. Without date information, it would not be possible to account for daylight-saving time changes.
When we provide a timestamp labeled as Eastern Standard Time, PostgreSQL adds 5 hours before saving it. This ensures that our database remains consistent, and our time stays accurate, even if we input data using different timezones.
Let’s add the scheduled_date column to our articles and use the TIMESTAMPTZ column type.
20231105221040_add_scheduled_date_to_articles.ts
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import { Kysely } from 'kysely'; export async function up(database: Kysely<unknown>): Promise<void> { await database.schema .alterTable('articles') .addColumn('scheduled_date', 'timestamptz') .execute(); } export async function down(database: Kysely<unknown>): Promise<void> { await database.schema.alterTable('articles').dropColumn('scheduled_date'); } |
Inserting the date into the database
To ensure the validity of the data our users provide, we can use the class-validator library. Kysely accepts data in either the Date class or as an ISO string. Let’s require the users to provide the ISO strings.
article.dto.ts
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import { IsString, IsNotEmpty, IsOptional, IsNumber, IsISO8601, } from 'class-validator'; export class ArticleDto { @IsString() @IsNotEmpty() title: string; @IsString({ each: true }) @IsNotEmpty({ each: true }) paragraphs: string[]; @IsOptional() @IsNumber({}, { each: true }) categoryIds?: number[]; @IsISO8601({ strict: true, }) @IsOptional() scheduledDate?: string; } |
The strict parameter ensures that the given date is valid, taking into account factors such as leap days.
Since we allow the users to provide the date as an ISO string, but retrieve it from the database using the Date class, we should use the ColumnType generic type.
articlesTable.ts
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import { ColumnType, Generated } from 'kysely'; export interface ArticlesTable { id: Generated<number>; title: string; paragraphs: string[]; author_id: number; created_at?: Date; scheduled_date?: ColumnType<Date, string | Date, string | Date>; } |
The next step is to adjust our model.
article.model.ts
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export interface ArticleModelData { id: number; title: string; paragraphs: string[]; author_id: number; scheduled_date?: Date; } export class Article { id: number; title: string; paragraphs: string[]; authorId: number; scheduledDate?: Date; constructor({ id, title, paragraphs, author_id, scheduled_date, }: ArticleModelData) { this.id = id; this.title = title; this.paragraphs = paragraphs; this.authorId = author_id; if (scheduled_date) { this.scheduledDate = scheduled_date; } } } |
We can now use our new property when creating the articles.
articles.repository.ts
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import { Database } from '../database/database'; import { Article } from './article.model'; import { BadRequestException, Injectable } from '@nestjs/common'; import { ArticleDto } from './dto/article.dto'; import { PostgresErrorCode } from '../database/postgresErrorCode.enum'; import { isDatabaseError } from '../types/databaseError'; @Injectable() export class ArticlesRepository { constructor(private readonly database: Database) {} async create(data: ArticleDto, authorId: number) { try { const databaseResponse = await this.database .insertInto('articles') .values({ title: data.title, paragraphs: data.paragraphs, author_id: authorId, scheduled_date: data.scheduledDate, }) .returningAll() .executeTakeFirstOrThrow(); return new Article(databaseResponse); } catch (error) { if (!isDatabaseError(error)) { throw error; } if (error.code === PostgresErrorCode.CheckViolation) { throw new BadRequestException( 'The length of the content needs to be greater than 0', ); } if (error.code === PostgresErrorCode.NotNullViolation) { throw new BadRequestException( `A null value can't be set for the ${error.column} column`, ); } throw error; } } // ... } |
Default values
We do not always have to provide the date manually. Instead, let’s adjust our migration that adds the created_at column.
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import { Kysely, sql } from 'kysely'; export async function up(database: Kysely<unknown>): Promise<void> { await database.schema .alterTable('articles') .addColumn('created_at', 'timestamptz', (column) => { return column.notNull().defaultTo(sql`now()`); }) .execute(); } export async function down(database: Kysely<unknown>): Promise<void> { await database.schema.alterTable('articles').dropColumn('created_at'); } |
Above, we use the now() function built into PostgreSQL to provide the default value for the created_at column. Since we provide a default value, we can also make this column non-nullable and don’t worry about the articles we already have in the database.
Summary
In this article, we’ve explored different methods for storing date and time data with PostgreSQL. We’ve also learned how to use Kysely to define various types of date columns in our schema. Besides that, we’ve used the class-validator library to validate the dates provided through the API.
Timezones can be the source of various bugs and problems. By utilizing the timestamp with timezone type in PostgreSQL, we can maintain data consistency, regardless of the time zones in which our users provide the data. Thanks to that, we can minimize the chance of timezone-related issues.