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TencentDB for PostgreSQL

Release Notes and Announcements
Release Notes
Product Announcements
Product Introduction
Overview
Features
Strengths
Scenarios
Information Security
Regions and AZs
Product Feature List
Large version lifecycle description
MSSQL Compatible Version
Billing
Billing Overview
Instance Type and Specification
Purchase Methods
Refund
Overdue Payments
Backup Space Billing
Database Audit Billing Overview
Getting Started
Creating TencentDB for PostgreSQL Instance
Connecting to TencentDB for PostgreSQL Instance
Managing TencentDB for PostgreSQL Instance
Importing Data
Migrating Data with DTS
Kernel Version Introduction
Kernel Version Overview
Kernel Version Release Notes
Viewing Kernel Version
Proprietary Kernel Features
Database Audit
Audit Service Description
Activating Audit Service
View Audit Logs
Modify audit services
Audit Performance Description
User Guide
Instance Management
Upgrading Instance
CPU Elastic Scaling
Read-Only Instance
Account Management
Database Management
Parameter Management
Log Management and Analysis
Backup and Restoration
Data Migration
Extension Management
Network Management
Access Management
Data Security
Tenant and Resource Isolation
Security Groups
Monitoring and Alarms
Tag
AI Practice
Using the Tencentdb_ai Plug-In to Call Large Models
Building Ai Applications with the Tencentdb Ai Plug-In
Combining Supabase to Quickly Build Backend Service Based on TencentDB for PostgreSQL
Use Cases
postgres_fdw Extension for Cross-database Access
Automatically Creating Partition in PostgreSQL
Searching in High Numbers of Tags Based on pg_roaringbitmap
Querying People Nearby with One SQL Statement
Configuring TencentDB for PostgreSQL as GitLab's External Data Source
Supporting Tiered Storage Based on cos_fdw Extension
Implement Read/Write Separation via pgpool
Implementing Slow SQL Analysis Using the Auto_explain Plugin
Using pglogical for Logical Replication
Using Debezium to Collect PostgreSQL Data
Set Up a Remote Disaster Recovery Environment for PostgreSQL Locally on CVM
Read-Only Instance and Read-Only Group Practical Tutorial
How to Use SCF for Scheduled Database Operations
Fix Table Bloat
Performance White Paper
Test Methods
Test Results
API Documentation
History
Introduction
API Category
Making API Requests
Instance APIs
Read-Only Instance APIs
Backup and Recovery APIs
Parameter Management APIs
Security Group APIs
Performance Optimization APIs
Account APIs
Specification APIs
Network APIs
Data Types
Error Codes
FAQs
Service Agreement
Service Level Agreement
Terms of Service
Glossary
Contact Us
DocumentaçãoTencentDB for PostgreSQLProduct IntroductionScenarios

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Última atualização: 2026-02-09 11:36:31

Enterprise Databases

Applications such as ERP, trading systems and financial systems need to handle sensitive data such as fund and customer information. Therefore, they require no data loss and complex business logics. With PostgreSQL as the underlying storage system, you can achieve high availability with data consistency, and implement complex business logics with simple programming languages.

Applications with LBS

Large games, O2O and other applications need to support such capabilities as world map, nearby stores, distance between two points, etc. PostGIS provides additional support for geographic objects, allowing you to run location queries with SQL without the need of complex programming languages, so that you can simplify your business logics, easily implement LBS, and increase the user stickiness.

Data Warehouse and Big Data

With more data types and powerful computing capability, PostgreSQL makes it easier for you to build a data warehouse or a big data analytics platform, so as to maximize your business operation value.

Website or App Development

Featuring good performance and powerful capabilities, PostgreSQL can effectively improve website performance and reduce development difficulty.
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