Difference between ActiveMQ and RabbitMQ | ActiveMQ Vs RabbitMQ

ActiveMQ and RabbitMQ are two of the widely used message queues used in the software industry.

In this article, we will be the differences between the two technologies.

ActiveMQ:

• ActiveMQ is used in enterprise projects to store multiple instances and supports clustering environments.
• ActiveMQ is programmed in Java
• ActiveMQ is developed by the Apache Software Foundation
• ActiveMQ supports C, C#, Haxe, Node.js, Perl, Racket, Python, and Ruby on Rails.
• OpenWire, Stomp, WSIF, WS, AUTO, AMQP and MQTT are the applied protocols in ActiveMQ.
• It can be implemented with two brokers along with P2P architecture.
• It is a multi-protocol-supported message broker.
• PUB-SUB and message queues are available message patterns.

RabbitMQ:

• RabbitMQ is a message broker which is executed in low-level AMQP protocol and acts as an intermediator between two applications in the communication process.
• RabbitMQ is written in Erlang or OTP language.
• RabbitMQ is developed by Pivotal Software under the Mozilla Public License.
• RabbitMQ supports multiple languages such as Java, Ruby, Python, PHP, Perl Rust, Go, JavaScript, C, and C++.
• HTTP, MQTT, STOMP, and AMQP are the implemented protocols in RabbitMQ
• One broker is required.
• RabbitMQ works on the management plugin.
• It has general message patterns such as Message Queue, PUB-SUB and RPC, and Routing.

Difference between Apache Kafka and Apache Flume | Kafka Vs Flume

Apache Kafka and Apache Flume are two of the most widely used technologies for data ingestion and centralized data storage respectively

In this article, we will be looking at the difference between Apache Kafka and Apache Flume.

Apache Kafka:

• Apache Kafka is a distributed data system.
  
• Kafka is optimized for ingesting and processing streaming data in real time.
  
• Kafka basically works as a pull model.
  
• Kafka is easy to scale.
  
• Kafka is a fault-tolerant, efficient, and scalable messaging system.
  
• Kafka supports automatic recovery if resilient to node failure.
  
• Kafka runs as a cluster that handles the incoming high-volume data streams in real time.
  
• Kafka will treat each topic partition as an ordered set of messages.

Apache Flume:

• Apache Flume is an available, reliable, and distributed system.
  
• Flume is efficiently collecting, aggregating, and moving large amounts of log data from many different sources to a centralized data store.
  
• Flume basically works as a push model
  
• Flume is not scalable in comparison with Kafka.
  
• Flume is specially designed for Hadoop.
  
• You will lose events in the channel in case of flume-agent failure.
  
• Flume is a tool to collect log data from distributed web servers.
  
• Flume can take in streaming data from multiple sources for storage and analysis which use in Hadoop.