ActiveMQ vs Confluent

Overview

ActiveMQ

Stacks615

Followers1.3K

Votes77

GitHub Stars2.4K

Forks1.5K

Confluent

Stacks250

Followers239

Votes14

ActiveMQ vs Confluent: 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 Confluent? We make a stream data platform to help companies harness their high volume real-time data streams. It is a data streaming platform based on Apache Kafka: a full-scale streaming platform, capable of not only publish-and-subscribe, but also the storage and processing of data within the stream.

ActiveMQ belongs to "Message Queue" category of the tech stack, while Confluent can be primarily classified under "Stream Processing".

ActiveMQ is an open source tool with 1.53K GitHub stars and 1.06K GitHub forks. Here's a link to ActiveMQ's open source repository on GitHub.

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Detailed Comparison

ActiveMQ	Confluent
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.	It is a data streaming platform based on Apache Kafka: a full-scale streaming platform, capable of not only publish-and-subscribe, but also the storage and processing of data within the stream
Protect your data & Balance your Load; Easy enterprise integration patterns; Flexible deployment	Reliable; High-performance stream data platform; Manage and organize data from different sources.
Statistics
GitHub Stars 2.4K	GitHub Stars -
GitHub Forks 1.5K	GitHub Forks -
Stacks 615	Stacks 250
Followers 1.3K	Followers 239
Votes 77	Votes 14
Pros & Cons
Pros 18 Easy to use 14 Open source 13 Efficient 10 JMS compliant 6 High Availability Cons 1 Low resilience to exceptions and interruptions 1 ONLY Vertically Scalable 1 Support 1 Difficult to scale	Pros 4 Free for casual use 3 Dashboard for kafka insight 3 No hypercloud lock-in 2 Easily scalable 2 Zero devops Cons 1 Proprietary
Integrations
No integrations available	Microsoft SharePoint Java Python Salesforce Sales Cloud Kafka Streams

What are some alternatives to ActiveMQ, Confluent?

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

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

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 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

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

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 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

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

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.