Software Alternatives, Accelerators & Startups

CloudAMQP VS Google Cloud Dataproc

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

CloudAMQP logo CloudAMQP

CloudAMQP automates every part of setup, running and scaling of RabbitMQ clusters. Available on all major cloud and application platforms.

Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
  • CloudAMQP Landing page
    Landing page //
    2023-07-04
  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09

CloudAMQP videos

No CloudAMQP videos yet. You could help us improve this page by suggesting one.

+ Add video

Google Cloud Dataproc videos

Dataproc

Category Popularity

0-100% (relative to CloudAMQP and Google Cloud Dataproc)
Stream Processing
100 100%
0% 0
Data Dashboard
0 0%
100% 100
Data Integration
100 100%
0% 0
Big Data
0 0%
100% 100

User comments

Share your experience with using CloudAMQP and Google Cloud Dataproc. For example, how are they different and which one is better?
Log in or Post with

Social recommendations and mentions

Based on our record, Google Cloud Dataproc should be more popular than CloudAMQP. 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.

CloudAMQP mentions (2)

  • Architecture for processing thousands of images upon a single request
    RabbitMQ dude! Spin up a free instance on cloudamqp.com (not affiliated, but I use them in prod - free instances already are enough for many use cases), throw a bunch of consumers in the queue, push as many jobs as you want and you'll have an awesome indestructible working process. Source: about 2 years ago
  • Parcel Tracking Application With RabbitMQ
    We can prefer to install RabbitMQ on our local machine but in that case, the installation steps would be different from the operating system to the operating system and we would need to mess with some network settings. Therefore, we make this step with http://cloudamqp.com. To do that let's create https://cloudamqp.com. Later on, click on the button Create New Instance and create a new message broker instance. We... - Source: dev.to / about 3 years ago

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 CloudAMQP and Google Cloud Dataproc, you can also consider the following products

RabbitMQ - RabbitMQ is an open source message broker software.

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

ZeroMQ - ZeroMQ is a high-performance asynchronous messaging library.

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

Amazon MQ - Amazon MQ is a managed message broker service for ActiveMQ that makes it easy to set up and operate message brokers in the cloud. Easily migrate messaging.

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