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  5. Apache Pulsar vs MQTT

Apache Pulsar vs MQTT

OverviewComparisonAlternatives

Overview

MQTT
MQTT
Stacks635
Followers577
Votes7
Apache Pulsar
Apache Pulsar
Stacks118
Followers199
Votes24

Apache Pulsar vs MQTT: What are the differences?

Introduction

Apache Pulsar and MQTT are both messaging protocols used for communication between applications and devices. While they have some similarities, such as being lightweight and supporting publish-subscribe messaging patterns, there are key differences that set them apart.

  1. Scalability: One of the major differences between Apache Pulsar and MQTT is in terms of scalability. Apache Pulsar is designed to be highly scalable, being able to handle large message volumes and support thousands of topics and subscriptions. It achieves this through the use of a multi-layered, hierarchical architecture that allows for efficient data routing and load balancing. MQTT, on the other hand, lacks such a hierarchical design and may face challenges in scaling to handle larger deployments.

  2. Persistent Storage: Another important distinction is in the way Apache Pulsar and MQTT handle message persistence. Apache Pulsar provides built-in support for persistent storage of messages, allowing them to be stored on disk and retrieved even in the event of a failure. This makes it more suitable for scenarios where message durability is critical, such as in financial systems or IoT applications. MQTT, on the other hand, does not have native support for persistent storage and relies on external mechanisms to ensure message persistence.

  3. Message Acknowledgement: Apache Pulsar and MQTT differ in their approach to message acknowledgement. In Apache Pulsar, messages are acknowledged on a per-consumer basis, meaning that each consumer in a subscription group acknowledges the messages it has consumed. This allows for fine-grained control over message acknowledgement and can help avoid message duplication. In MQTT, acknowledgement happens at the individual message level, where each message needs to be explicitly acknowledged by the consumer. This approach provides more flexibility but may require additional logic to handle message deduplication.

  4. Schema and Type Support: Apache Pulsar provides built-in support for schema and type enforcement, allowing for the definition of a schema for the messages being exchanged. This ensures that messages conform to a specific structure and data type, enabling strong data validation and compatibility checks. MQTT, on the other hand, does not have native support for schema and type enforcement, and message validation needs to be implemented externally.

  5. Brokers and Topics: Apache Pulsar and MQTT differ in their terminology and concepts of brokers and topics. In Apache Pulsar, brokers are responsible for message storage and distribution, while topics represent the logical channels for message exchange. MQTT, on the other hand, uses the concept of a broker to facilitate communication between publishers and subscribers, with topics representing the specific subjects of interest.

  6. Supported Programming Languages: Another notable difference is in the programming languages supported by Apache Pulsar and MQTT. Apache Pulsar provides client libraries for a wide range of languages, including Java, Python, Go, and C++. This allows developers to use their preferred language for building applications on top of Apache Pulsar. MQTT also supports multiple programming languages, with client libraries available for popular languages such as C, Java, and Python.

In summary, Apache Pulsar and MQTT differ in terms of scalability, persistent storage, message acknowledgement, schema support, broker and topic concepts, and supported programming languages.

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Detailed Comparison

MQTT
MQTT
Apache Pulsar
Apache Pulsar

It was designed as an extremely lightweight publish/subscribe messaging transport. It is useful for connections with remote locations where a small code footprint is required and/or network bandwidth is at a premium.

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
635
Stacks
118
Followers
577
Followers
199
Votes
7
Votes
24
Pros & Cons
Pros
  • 3
    Varying levels of Quality of Service to fit a range of
  • 2
    Very easy to configure and use with open source tools
  • 2
    Lightweight with a relatively small data footprint
Cons
  • 1
    Easy to configure in an unsecure manner
Pros
  • 7
    Simple
  • 4
    Scalable
  • 3
    High-throughput
  • 2
    Geo-replication
  • 2
    Multi-tenancy
Cons
  • 1
    No one and only one delivery
  • 1
    Very few commercial vendors for support
  • 1
    LImited Language support(6)
  • 1
    Only Supports Topics
  • 1
    Not jms compliant

What are some alternatives to MQTT, 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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