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  4. Message Queue
  5. ActiveMQ vs Apache Pulsar

ActiveMQ vs Apache Pulsar

OverviewComparisonAlternatives

Overview

ActiveMQ
ActiveMQ
Stacks879
Followers1.3K
Votes77
GitHub Stars2.4K
Forks1.5K
Apache Pulsar
Apache Pulsar
Stacks118
Followers199
Votes24

ActiveMQ vs Apache Pulsar: What are the differences?

Introduction In this article, we will explore the key differences between ActiveMQ and Apache Pulsar, two popular messaging systems used in distributed applications.

  1. Message Model: ActiveMQ follows the traditional publish-subscribe and point-to-point messaging models, where messages are sent to a topic or a queue respectively. On the other hand, Apache Pulsar introduces the concept of a "topic" which can support both publish-subscribe and event streaming paradigms, allowing for greater flexibility in message distribution.

  2. Architecture: ActiveMQ is based on the Java Message Service (JMS) standard and is built using a classic broker-based architecture. It uses a central broker to handle message routing and delivery. In contrast, Apache Pulsar adopts a distributed messaging architecture, using the powerful concept of "bookies" that store and replicate messages across multiple nodes, ensuring high availability and fault tolerance.

  3. Scalability and Performance: ActiveMQ has limitations in terms of scalability as it relies on a single broker for message handling. It can suffer from performance bottlenecks when dealing with a large number of messages and high throughput. In contrast, Apache Pulsar has a highly scalable and performant architecture, providing seamless horizontal scalability by allowing independent scaling of compute and storage resources. This makes Pulsar more suitable for handling massive workloads.

  4. Multi-Tenancy: ActiveMQ doesn't natively support multi-tenancy, which means it is not efficient for hosting multiple isolated messaging environments within a single deployment. On the other hand, Apache Pulsar has built-in support for multi-tenancy, enabling organizations to create separate namespaces, topics, and access control policies for different departments or teams, enhancing resource isolation and security.

  5. Message Durability: ActiveMQ provides message durability through features like persistent messaging and durable subscriptions. However, it relies on traditional storage options like disk-based storage, which can impact performance in certain scenarios. Apache Pulsar, on the other hand, uses a powerful combination of in-memory and durable storage for messages, ensuring high-speed message persistence without sacrificing performance.

  6. Compatibility and Ecosystem: ActiveMQ supports the JMS standard and provides extensive support for integration with various Java-based frameworks and applications. It also has support for other protocols like AMQP and MQTT. Apache Pulsar, in addition to supporting the Pulsar-native messaging protocol, provides compatibility with the Apache Kafka API, allowing seamless migration of existing Kafka applications to Pulsar.

In summary, ActiveMQ and Apache Pulsar differ in terms of their message models, architecture, scalability, multi-tenancy support, message durability, and compatibility with other systems. Apache Pulsar offers a more modern and scalable messaging architecture with enhanced features like multi-tenancy and better performance, making it a suitable choice for demanding distributed applications.

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Detailed Comparison

ActiveMQ
ActiveMQ
Apache Pulsar
Apache Pulsar

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.

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.

Protect your data & Balance your Load; Easy enterprise integration patterns; Flexible deployment
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
GitHub Stars
2.4K
GitHub Stars
-
GitHub Forks
1.5K
GitHub Forks
-
Stacks
879
Stacks
118
Followers
1.3K
Followers
199
Votes
77
Votes
24
Pros & Cons
Pros
  • 18
    Easy to use
  • 14
    Open source
  • 13
    Efficient
  • 10
    JMS compliant
  • 6
    High Availability
Cons
  • 1
    Support
  • 1
    Difficult to scale
  • 1
    Low resilience to exceptions and interruptions
  • 1
    ONLY Vertically Scalable
Pros
  • 7
    Simple
  • 4
    Scalable
  • 3
    High-throughput
  • 2
    Multi-tenancy
  • 2
    Geo-replication
Cons
  • 1
    Only Supports Topics
  • 1
    Not jms compliant
  • 1
    No guaranteed dliefvery
  • 1
    No one and only one delivery
  • 1
    LImited Language support(6)

What are some alternatives to ActiveMQ, 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.

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.

IronMQ

IronMQ

An easy-to-use highly available message queuing service. Built for distributed cloud applications with critical messaging needs. Provides on-demand message queuing with advanced features and cloud-optimized performance.

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