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TDMQ for Apache Pulsar

Release Notes and Announcements
Release Notes
Cluster Version Updates
Product Announcements
Product Introduction
Introduction and Selection of the TDMQ Product Series
What Is TDMQ for Apache Pulsar
Strengths
Scenarios
How It Works
Product Series
Version Support Instructions for Open-Source Apache Pulsar
Comparison with Open-Source Apache Pulsar
High Availability
Quotas and Limits
Basic Concepts
Billing
Billing Overview
Pricing
Billing Examples
Renewal
Viewing Consumption Details
Overdue Payments
Refund
Getting Started
Getting Started Guide
Preparations
Using the SDK to Send and Receive General Messages
Using the SDK to Send and Receive Advanced Feature Messages
User Guide
Usage Process Guide
Configuring the Account Permission
Creating a Cluster
Configuring the Namespace
Configuring the Topic
Connecting to a Cluster
Managing the Cluster
Querying Messages and Traces
Cross-Region Replication
Viewing Monitoring Data and Configuring Alarm Rules
Use Cases
Client Usage
Abnormal Consumer Isolation
Traffic Throttling Mechanisms
Transaction Reconciliation
Message Idempotence
Message Compression
Migration Guide
Single-Write Multiple-Read Cluster Migration Solutions
Hitless Migration from Virtual Cluster to Pro Cluster
SDK Reference
API Overview
SDK Reference
SDK Overview
Recommended SDK Configuration Parameters
TCP Protocol (Apache Pulsar)
Security and Compliance
Permission Management
Deletion Protection
CloudAudit
FAQs
Monitoring
Clients
Agreements
Service Level Agreement
TDMQ Policy
Contact Us
Glossary

Strengths

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Last updated: 2025-12-24 14:51:17

Strong Data Consistency

TDMQ for Apache Pulsar achieves strong data consistency by using the BookKeeper consistency protocol (similar to the RAFT algorithm). Message data is backed up to different physical servers and flushed to the disk synchronously. When a physical server is faulty, the data replication mechanism in the background can quickly migrate data to ensure user data backup availability.

High Performance and Low Latency

TDMQ for Apache Pulsar efficiently supports million-level message production and consumption, with a massive message backlog capacity without an upper limit, supporting all Tencent billing scenarios. In terms of performance, the QPS of a single cluster exceeds 100,000, and protective mechanisms are provided for time consumption to ensure low latency, helping you easily meet business performance requirements.

Million-Level Topics

TDMQ for Apache Pulsar adopts the compute-storage separation architecture, making it easy to support million-level message topics. Compared with other message queue (MQ) products on the market, TDMQ for Apache Pulsar will not experience a sharp decline in performance due to an increase in the number of topics.

Abundant Message Types

TDMQ for Apache Pulsar provides various message types, covering general messages, sequential messages (globally sequential/partitioned sequential), and scheduled messages, meeting advanced feature requirements in various strict scenarios.

Unlimited Number of Consumers

Unlike the message consumption mode of Kafka, the number of consumers of TDMQ for Apache Pulsar is not limited by the number of partitions in a topic, and the message volume per consumer is balanced based on a certain algorithm. Businesses can start consumers as required.

Isolation Control

TDMQ for Apache Pulsar provides a mechanism to isolate topics by tenant, and can precisely control the production and consumption rates of each tenant, ensuring that tenants do not affect each other and avoiding resource contention in message processing.

Global Deployment

TDMQ for Apache Pulsar supports global deployment, allowing enterprises with global businesses to purchase services in nearby regions.

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