Software Alternatives & Reviews

Apache Beam VS RabbitMQ

Compare Apache Beam VS RabbitMQ and see what are their differences

Apache Beam logo Apache Beam

Apache Beam provides an advanced unified programming model to implement batch and streaming data processing jobs.

RabbitMQ logo RabbitMQ

RabbitMQ is an open source message broker software.
  • Apache Beam Landing page
    Landing page //
    2022-03-31
  • RabbitMQ Landing page
    Landing page //
    2023-10-03

Apache Beam videos

How to Write Batch or Streaming Data Pipelines with Apache Beam in 15 mins with James Malone

More videos:

  • Review - Best practices towards a production-ready pipeline with Apache Beam
  • Review - Streaming data into Apache Beam with Kafka

RabbitMQ videos

數據工程 | 快速review | 如何架設Docker Swarm + RabbitMQ??

More videos:

  • Review - What's New in RabbitMQ—June 2012 Edition
  • Review - Feature complete: Uncovering the true cost different RabbitMQ features and configs - Jack Vanlightly

Category Popularity

0-100% (relative to Apache Beam and RabbitMQ)
Big Data
100 100%
0% 0
Data Integration
0 0%
100% 100
Data Dashboard
100 100%
0% 0
Web Service Automation
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Beam and RabbitMQ

Apache Beam Reviews

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RabbitMQ Reviews

Best message queue for cloud-native apps
RabbitMQ is an open-source message broker software that allows applications to communicate with each other using a messaging protocol. It was developed by Rabbit Technologies and first released in 2007, which was later acquired by VMware.RabbitMQ is based on the Advanced Message Queuing Protocol (AMQP) and provides a reliable, scalable, and interoperable messaging system.
Source: docs.vanus.ai
Are Free, Open-Source Message Queues Right For You?
However, it's important to note that every tool has its strengths and use cases. For instance, Kafka's strength lies in real-time data streaming, NATS shines with its simplicity, and RabbitMQ provides support for complex routing. In contrast, IronMQ provides an excellent balance of simplicity, durability, scalability, and ease of management, making it a powerful choice for...
Source: blog.iron.io
NATS vs RabbitMQ vs NSQ vs Kafka | Gcore
RabbitMQ follows a standard store-and-forward pattern, allowing messages to be stored in RAM, on disk, or both. To ensure the persistence of messages, the producer can tag them as persistent, and they will be stored in a separate queue. This helps achieve message retention even after a restart or failure of the RabbitMQ server.
Source: gcore.com
6 Best Kafka Alternatives: 2022’s Must-know List
Due to RabbitMQ’s lightweight design, it can be easily deployed on public and private clouds. RabbitMQ is backed not only by a robust support system but also offers a great developer community. Since it is open-source software it is one of the best Kafka Alternatives and RabbitMQ is free of cost.
Source: hevodata.com
Top 15 Alternatives to RabbitMQ In 2021
In this article, we will discuss an overview on RabbitMQ Alternatives. RabbitMQ has a flexible messaging system and functions as a multipurpose broker. But it often stops working, because of its high latency and very slow while doing so. The deployment & management of RabbitMQ is a too dull procedure. It can not be installed as modules, it can be installed only on machines...
Source: gokicker.com

Social recommendations and mentions

Based on our record, Apache Beam seems to be a lot more popular than RabbitMQ. While we know about 14 links to Apache Beam, we've tracked only 1 mention of RabbitMQ. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Apache Beam mentions (14)

  • Ask HN: Does (or why does) anyone use MapReduce anymore?
    The "streaming systems" book answers your question and more: https://www.oreilly.com/library/view/streaming-systems/9781491983867/. It gives you a history of how batch processing started with MapReduce, and how attempts at scaling by moving towards streaming systems gave us all the subsequent frameworks (Spark, Beam, etc.). As for the framework called MapReduce, it isn't used much, but its descendant... - Source: Hacker News / 3 months ago
  • How do Streaming Aggregation Pipelines work?
    Apache Beam is one of many tools that you can use. Source: 5 months ago
  • Real Time Data Infra Stack
    Apache Beam: Streaming framework which can be run on several runner such as Apache Flink and GCP Dataflow. - Source: dev.to / over 1 year ago
  • Google Cloud Reference
    Apache Beam: Batch/streaming data processing 🔗Link. - Source: dev.to / over 1 year ago
  • Composer out of resources - "INFO Task exited with return code Negsignal.SIGKILL"
    What you are looking for is Dataflow. It can be a bit tricky to wrap your head around at first, but I highly suggest leaning into this technology for most of your data engineering needs. It's based on the open source Apache Beam framework that originated at Google. We use an internal version of this system at Google for virtually all of our pipeline tasks, from a few GB, to Exabyte scale systems -- it can do it all. Source: over 1 year ago
View more

RabbitMQ mentions (1)

What are some alternatives?

When comparing Apache Beam and RabbitMQ, you can also consider the following products

Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

Apache ActiveMQ - Apache ActiveMQ is an open source messaging and integration patterns server.

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

IBM MQ - IBM MQ is messaging middleware that simplifies and accelerates the integration of diverse applications and data across multiple platforms.