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RabbitMQ VS Google Cloud Dataproc

Compare RabbitMQ VS Google Cloud Dataproc and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

RabbitMQ logo RabbitMQ

RabbitMQ is an open source message broker software.

Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
  • RabbitMQ Landing page
    Landing page //
    2023-10-03
  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09

RabbitMQ videos

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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

Google Cloud Dataproc videos

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Dataproc

Category Popularity

0-100% (relative to RabbitMQ and Google Cloud Dataproc)

RabbitMQ

Google Cloud Dataproc

Data Integration
100 100%
Data Integration
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Web Service Automation
100 100%
Web Service Automation
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using RabbitMQ and Google Cloud Dataproc. For example, how are they different and which one is better?
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Reviews

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

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

Google Cloud Dataproc Reviews

We have no reviews of Google Cloud Dataproc yet.
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Social recommendations and mentions

Based on our record, Google Cloud Dataproc should be more popular than RabbitMQ. It has been mentiond 3 times since March 2021. 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.

RabbitMQ mentions (1)

Google Cloud Dataproc mentions (3)

  • Connecting IPython notebook to spark master running in different machines
    I have also a spark cluster created with google cloud dataproc. Source: about 1 year ago
  • Why we don’t use Spark
    Specifically, we heavily rely on managed services from our cloud provider, Google Cloud Platform (GCP), for hosting our data in managed databases like BigTable and Spanner. For data transformations, we initially heavily relied on DataProc - a managed service from Google to manage a Spark cluster. - Source: dev.to / about 2 years ago
  • Data processing issue
    With that, the best way to maximize processing and minimize time is to use Dataflow or Dataproc depending on your needs. These systems are highly parallel and clustered, which allows for much larger processing pipelines that execute quickly. Source: over 2 years ago

What are some alternatives?

When comparing RabbitMQ and Google Cloud Dataproc, you can also consider the following products

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

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.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

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

HortonWorks Data Platform - The Hortonworks Data Platform is a 100% open source distribution of Apache Hadoop that is truly...

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