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  5. Apache Pulsar vs Apache RocketMQ

Apache Pulsar vs Apache RocketMQ

OverviewComparisonAlternatives

Overview

Apache RocketMQ
Apache RocketMQ
Stacks48
Followers200
Votes8
Apache Pulsar
Apache Pulsar
Stacks119
Followers199
Votes24

Apache Pulsar vs Apache RocketMQ: What are the differences?

Introduction

Apache Pulsar and Apache RocketMQ are both open-source messaging systems used for building real-time streaming applications. While they share some similarities, there are key differences between the two.

  1. Messaging Model: Apache Pulsar follows a publish-subscribe messaging model, where publishers and subscribers communicate through topics. It supports both one-to-many and many-to-many communication patterns. In contrast, Apache RocketMQ follows a distributed messaging model, with producers sending messages to specific queues or topics, and consumers pulling messages from these queues or topics.

  2. Scale and Scalability: Apache Pulsar is designed to be inherently scalable, allowing seamless horizontal scalability across multiple clusters. It provides built-in support for multi-tenancy and efficient data replication. On the other hand, Apache RocketMQ is also scalable, but it focuses more on vertical scalability within a single cluster by supporting partitioning and sharding of topics.

  3. Persistence and Durability: Apache Pulsar offers persistent message storage by default, ensuring durability even in the presence of failures. It utilizes a tiered storage architecture with a combination of off-heap, on-heap, and disk storage. Apache RocketMQ, on the other hand, supports both persistent and non-persistent messaging, but it primarily focuses on providing high throughput rather than strong durability guarantees.

  4. Message Ordering: Apache Pulsar guarantees strict message ordering within a partition, enabling reliable FIFO processing. It ensures that messages published to a topic are consumed in the same order they were published. In contrast, Apache RocketMQ provides a more relaxed ordering guarantee, allowing out-of-order message consumption within a topic.

  5. Cross Datacenter Replication: Apache Pulsar has native support for replicating data across multiple datacenters, providing seamless disaster recovery and geo-distribution capabilities. It ensures strong consistency between datacenters. Conversely, Apache RocketMQ relies on third-party solutions or custom implementations for cross-datacenter replication.

  6. Ecosystem and Community: Apache Pulsar has a growing ecosystem with a diverse set of connectors, integrations, and tools. It is backed by a vibrant and active community, which contributes to its rapid development. Apache RocketMQ also has a strong ecosystem and community support, but it may have a relatively smaller community compared to Apache Pulsar.

In summary, Apache Pulsar and Apache RocketMQ differ in their messaging models, scalability approaches, durability guarantees, message ordering, cross-datacenter replication support, and ecosystem/community size.

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Detailed Comparison

Apache RocketMQ
Apache RocketMQ
Apache Pulsar
Apache Pulsar

Apache RocketMQ is a distributed messaging and streaming platform with low latency, high performance and reliability, trillion-level capacity and flexible scalability.

Apache Pulsar is a distributed messaging solution developed and released to open source at Yahoo. Pulsar supports both pub-sub messaging and queuing in a platform designed for performance, scalability, and ease of development and operation.

-
Unified model supporting pub-sub messaging and queuing; Easy scalability to millions of topics; Native multi-datacenter replication; Multi-language client API; Guaranteed data durability; Scalable distributed storage leveraging Apache BookKeeper
Statistics
Stacks
48
Stacks
119
Followers
200
Followers
199
Votes
8
Votes
24
Pros & Cons
Pros
  • 2
    Support tracing message and transactional message
  • 2
    Million-level message accumulation capacity in a single
  • 1
    BigData Friendly
  • 1
    Feature-rich administrative dashboard for configuration
  • 1
    Low latency
Pros
  • 7
    Simple
  • 4
    Scalable
  • 3
    High-throughput
  • 2
    Geo-replication
  • 2
    Multi-tenancy
Cons
  • 1
    Only Supports Topics
  • 1
    Not jms compliant
  • 1
    No guaranteed dliefvery
  • 1
    LImited Language support(6)
  • 1
    Very few commercial vendors for support
Integrations
Docker
Docker
No integrations available

What are some alternatives to Apache RocketMQ, Apache Pulsar?

Kafka

Kafka

Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

RabbitMQ

RabbitMQ

RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.

Celery

Celery

Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well.

Amazon SQS

Amazon SQS

Transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be always available. With SQS, you can offload the administrative burden of operating and scaling a highly available messaging cluster, while paying a low price for only what you use.

NSQ

NSQ

NSQ is a realtime distributed messaging platform designed to operate at scale, handling billions of messages per day. It promotes distributed and decentralized topologies without single points of failure, enabling fault tolerance and high availability coupled with a reliable message delivery guarantee. See features & guarantees.

ActiveMQ

ActiveMQ

Apache ActiveMQ is fast, supports many Cross Language Clients and Protocols, comes with easy to use Enterprise Integration Patterns and many advanced features while fully supporting JMS 1.1 and J2EE 1.4. Apache ActiveMQ is released under the Apache 2.0 License.

ZeroMQ

ZeroMQ

The 0MQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. 0MQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more.

Apache NiFi

Apache NiFi

An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.

Gearman

Gearman

Gearman allows you to do work in parallel, to load balance processing, and to call functions between languages. It can be used in a variety of applications, from high-availability web sites to the transport of database replication events.

Memphis

Memphis

Highly scalable and effortless data streaming platform. Made to enable developers and data teams to collaborate and build real-time and streaming apps fast.

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