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  1. Stackups
  2. Utilities
  3. Background Jobs
  4. Message Queue
  5. ActiveMQ vs Apollo

ActiveMQ vs Apollo

OverviewComparisonAlternatives

Overview

ActiveMQ
ActiveMQ
Stacks879
Followers1.3K
Votes77
GitHub Stars2.4K
Forks1.5K
Apollo
Apollo
Stacks2.7K
Followers1.8K
Votes25

ActiveMQ vs Apollo: What are the differences?

Introduction

In this article, we will explore the key differences between ActiveMQ and Apollo, two popular messaging systems.

  1. Message Persistence: ActiveMQ stores messages in a journal or database using JDBC or file-based persistence. On the other hand, Apollo uses a database-backed message store that provides faster message persistence and recovery.

  2. Performance: ActiveMQ has limited scalability due to its use of Java Message Service (JMS) for communication. In contrast, Apollo is built on the Apache Foundation's NIO messaging support, allowing for higher performance and throughput.

  3. Protocols: ActiveMQ supports various protocols such as MQTT, STOMP, and WebSocket. Apollo primarily focuses on AMQP (Advanced Message Queuing Protocol) but also supports MQTT, STOMP, and HTTP.

  4. Configuration: ActiveMQ uses XML-based configuration, which can be complex and hard to manage. In contrast, Apollo uses a simple and flexible configuration file format that allows for easier setup and maintenance.

  5. Transports: ActiveMQ uses traditional TCP/IP-based transports for communication. Apollo, on the other hand, utilizes the WebSocket protocol, which enables real-time bidirectional communication between clients and servers over a single, long-lived connection.

  6. Clustering: ActiveMQ's clustering mechanism is primarily based on network connectors, which can be complex to configure and maintain. Apollo, on the other hand, provides a simpler and more flexible clustering mechanism using the concept of virtual hosts.

In summary, ActiveMQ and Apollo differ in terms of message persistence, performance, supported protocols, configuration, transports, and clustering mechanisms. These differences make each messaging system suitable for specific use cases based on requirements and preferences.

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Detailed Comparison

ActiveMQ
ActiveMQ
Apollo
Apollo

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.

Build a universal GraphQL API on top of your existing REST APIs, so you can ship new application features fast without waiting on backend changes.

Protect your data & Balance your Load; Easy enterprise integration patterns; Flexible deployment
-
Statistics
GitHub Stars
2.4K
GitHub Stars
-
GitHub Forks
1.5K
GitHub Forks
-
Stacks
879
Stacks
2.7K
Followers
1.3K
Followers
1.8K
Votes
77
Votes
25
Pros & Cons
Pros
  • 18
    Easy to use
  • 14
    Open source
  • 13
    Efficient
  • 10
    JMS compliant
  • 6
    High Availability
Cons
  • 1
    Support
  • 1
    ONLY Vertically Scalable
  • 1
    Difficult to scale
  • 1
    Low resilience to exceptions and interruptions
Pros
  • 12
    From the creators of Meteor
  • 8
    Great documentation
  • 3
    Open source
  • 2
    Real time if use subscription
Cons
  • 1
    File upload is not supported
  • 1
    Increase in complexity of implementing (subscription)
Integrations
No integrations available
GraphQL
GraphQL

What are some alternatives to ActiveMQ, Apollo?

Heroku

Heroku

Heroku is a cloud application platform – a new way of building and deploying web apps. Heroku lets app developers spend 100% of their time on their application code, not managing servers, deployment, ongoing operations, or scaling.

Clever Cloud

Clever Cloud

Clever Cloud is a polyglot cloud application platform. The service helps developers to build applications with many languages and services, with auto-scaling features and a true pay-as-you-go pricing model.

Google App Engine

Google App Engine

Google has a reputation for highly reliable, high performance infrastructure. With App Engine you can take advantage of the 10 years of knowledge Google has in running massively scalable, performance driven systems. App Engine applications are easy to build, easy to maintain, and easy to scale as your traffic and data storage needs grow.

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.

Red Hat OpenShift

Red Hat OpenShift

OpenShift is Red Hat's Cloud Computing Platform as a Service (PaaS) offering. OpenShift is an application platform in the cloud where application developers and teams can build, test, deploy, and run their applications.

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.

AWS Elastic Beanstalk

AWS Elastic Beanstalk

Once you upload your application, Elastic Beanstalk automatically handles the deployment details of capacity provisioning, load balancing, auto-scaling, and application health monitoring.

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.

Render

Render

Render is a unified platform to build and run all your apps and websites with free SSL, a global CDN, private networks and auto deploys from Git.

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