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  1. Stackups
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  4. Message Queue
  5. ActiveMQ vs Azure Storage

ActiveMQ vs Azure Storage

OverviewComparisonAlternatives

Overview

ActiveMQ
ActiveMQ
Stacks879
Followers1.3K
Votes77
GitHub Stars2.4K
Forks1.5K
Azure Storage
Azure Storage
Stacks1.3K
Followers787
Votes52

ActiveMQ vs Azure Storage: What are the differences?

What is ActiveMQ? A message broker written in Java together with a full JMS client. 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.

What is Azure Storage? Reliable, economical cloud storage for data big and small. Azure Storage provides the flexibility to store and retrieve large amounts of unstructured data, such as documents and media files with Azure Blobs; structured nosql based data with Azure Tables; reliable messages with Azure Queues, and use SMB based Azure Files for migrating on-premises applications to the cloud.

ActiveMQ can be classified as a tool in the "Message Queue" category, while Azure Storage is grouped under "Cloud Storage".

"Open source" is the primary reason why developers consider ActiveMQ over the competitors, whereas "All-in-one storage solution" was stated as the key factor in picking Azure Storage.

ActiveMQ is an open source tool with 1.51K GitHub stars and 1.05K GitHub forks. Here's a link to ActiveMQ's open source repository on GitHub.

According to the StackShare community, Azure Storage has a broader approval, being mentioned in 84 company stacks & 44 developers stacks; compared to ActiveMQ, which is listed in 33 company stacks and 17 developer stacks.

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Detailed Comparison

ActiveMQ
ActiveMQ
Azure Storage
Azure Storage

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.

Azure Storage provides the flexibility to store and retrieve large amounts of unstructured data, such as documents and media files with Azure Blobs; structured nosql based data with Azure Tables; reliable messages with Azure Queues, and use SMB based Azure Files for migrating on-premises applications to the cloud.

Protect your data & Balance your Load; Easy enterprise integration patterns; Flexible deployment
Blobs, Tables, Queues, and Files;Highly scalable;Durable & highly available;Premium Storage;Designed for developers
Statistics
GitHub Stars
2.4K
GitHub Stars
-
GitHub Forks
1.5K
GitHub Forks
-
Stacks
879
Stacks
1.3K
Followers
1.3K
Followers
787
Votes
77
Votes
52
Pros & Cons
Pros
  • 18
    Easy to use
  • 14
    Open source
  • 13
    Efficient
  • 10
    JMS compliant
  • 6
    High Availability
Cons
  • 1
    Difficult to scale
  • 1
    Support
  • 1
    ONLY Vertically Scalable
  • 1
    Low resilience to exceptions and interruptions
Pros
  • 24
    All-in-one storage solution
  • 15
    Pay only for data used regardless of disk size
  • 9
    Shared drive mapping
  • 2
    Cost-effective
  • 2
    Cheapest hot and cloud storage
Cons
  • 2
    Direct support is not provided by Azure storage
Integrations
No integrations available
Microsoft Azure
Microsoft Azure

What are some alternatives to ActiveMQ, Azure Storage?

Amazon S3

Amazon S3

Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web

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.

Amazon EBS

Amazon EBS

Amazon EBS volumes are network-attached, and persist independently from the life of an instance. Amazon EBS provides highly available, highly reliable, predictable storage volumes that can be attached to a running Amazon EC2 instance and exposed as a device within the instance. Amazon EBS is particularly suited for applications that require a database, file system, or access to raw block level storage.

Google Cloud Storage

Google Cloud Storage

Google Cloud Storage allows world-wide storing and retrieval of any amount of data and at any time. It provides a simple programming interface which enables developers to take advantage of Google's own reliable and fast networking infrastructure to perform data operations in a secure and cost effective manner. If expansion needs arise, developers can benefit from the scalability provided by Google's infrastructure.

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.

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