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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Google Cloud Dataflow

    Score9.1 out of 10
    N/AGoogle offers Cloud Dataflow, a managed streaming analytics platform for real-time data insights, fraud detection, and other purposes.N/A

    RabbitMQ

    Score9.5 out of 10
    N/ARabbitMQ, an open source message broker, is part of Pivotal Software, a VMware company acquired in 2019, and supports message queue, multiple messaging protocols, and more. RabbitMQ is available open source, however VMware also offers a range of commercial services for RabbitMQ; these are available as part of the Pivotal App Suite.N/A
    Pricing
    Google Cloud DataflowRabbitMQ
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    Google Cloud DataflowRabbitMQ
    Free Trial
    NoNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    Google Cloud DataflowRabbitMQ
    Considered Both Products
    Google
    No answer on this topic
    Open Source
    No answer on this topic
    Key User Insights
    Would buy again
    No answers on this topic
    91%
    Would buy again
    10 Answers
    Delivers good value for the price
    No answers on this topic
    100%
    Delivers good value for the price
    11 Answers
    Happy with the feature set
    No answers on this topic
    91%
    Happy with the feature set
    10 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    100%
    Lived up to sales and marketing promises
    7 Answers
    Implementation went as expected
    No answers on this topic
    100%
    Implementation went as expected
    11 Answers
    Features
    Google Cloud DataflowRabbitMQ
    Streaming Analytics
    Comparison of Streaming Analytics features of Google Cloud Dataflow and RabbitMQ
    Feature
    Google Cloud Dataflow
    7.3
    2 Ratings
    7% below category average
    RabbitMQ
    -
    Ratings
    Real-Time Data Analysis8.02 Ratings00 Ratings
    Visualization Dashboards5.01 Ratings00 Ratings
    Data Ingestion from Multiple Data Sources9.02 Ratings00 Ratings
    Low Latency9.02 Ratings00 Ratings
    Integrated Development Tools6.01 Ratings00 Ratings
    Data wrangling and preparation7.01 Ratings00 Ratings
    Linear Scale-Out8.02 Ratings00 Ratings
    Machine Learning Automation6.02 Ratings00 Ratings
    Data Enrichment8.02 Ratings00 Ratings
    Best Alternatives
    Google Cloud DataflowRabbitMQ
    Small Businesses
    Amazon Kinesis
    Score9.9 out of 10
    No answers on this topic
    Medium-sized Companies
    No answers on this topic
    Apache Kafka
    Score8.9 out of 10
    Enterprises
    Spotfire Streaming
    Score5 out of 10
    Apache Kafka
    Score8.9 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Google Cloud DataflowRabbitMQ
    Likelihood to Recommend
    9.0
    (2 ratings)
    9.9
    (11 ratings)
    Usability
    8.0
    (1 ratings)
    8.0
    (1 ratings)
    Support Rating
    -
    (0 ratings)
    6.5
    (4 ratings)
    User Testimonials
    Google Cloud DataflowRabbitMQ
    Likelihood to Recommend
    Google
    It is best in cases where you have batch as well as streaming data. Also in some cases where you have batch data right now and in future you will get streaming data. In those cases Dataflow is very good. Also in cases where most of your infra is on GCP. It might not be good when you already are on AWS or Azure. And also you want in-depth control over security and management. Then you can directly use Apache beam over Dataflow.
    Incentivized
    Read full review
    Open Source
    It is highly recommended that if you have microservices architecture and if you want to solve 2 phase commit issue, you should use RabbitMQ for communication between microservices. It is a quick and reliable mode of communication between microservices. It is also helpful if you want to implement a job and worker mechanism. You can push the jobs into RabbitMQ and that will be sent to the consumer. It is highly reliable so you won't miss any jobs and you can also implement a retry of jobs with the dead letter queue feature. It will be also helpful in time-consuming API. You can put time-consuming items into a queue so they will be processed later and your API will be quick.
    Incentivized
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    Pros
    Google
    • Streaming, Real time work load
    • Batch processing
    • Auto scaling
    • flexible pricing
    Read full review
    Open Source
    • What RabbitMQ does well is what it's advertised to do. It is good at providing lots of high volume, high availability queue. We've seen it handle upwards of 10 million messages in its queues, spread out over 200 queues before its publish/consume rates dipped. So yeah, it can definitely handle a lot of messages and a lot of queues. Depending on the size of the machine RabbitMQ is running on, I'm sure it can handle more.
    • Decent number of plugins! Want a plugin that gives you an interface to view all the queues and see their publish/consume rates? Yes, there's one for that. Want a plugin to "shovel" messages from one queue to another in an emergency? Check. Want a plugin that does extra logging for all the messages received? Got you covered!
    • Lots of configuration possibilities. We've tuned over 100 settings over the past year to get the performance and reliability just right. This could be a downside though--it's pretty confusing and some settings were hard to understand.
    Incentivized
    Read full review
    Cons
    Google
    • More templates for Bigquery and App Engine. There is only limited options for templates so the things we use can limit.
    • I would like native connectors for Excel (XLSX) to reduce the need for custom wrappers in financial pipelines.
    • Debugging Google Cloud Dataflow using only logs in Cloud Logging can be overwhelming sometimes, and it’s not always obvious which specific element in the flow caused a failure. IT uses a lot of time.
    Incentivized
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    Open Source
    • It breaks communication if we don't acknowledge early. In some cases our work items are time consuming that will take a time and in that scenario we are getting errors that RabbitMQ broke the channel. It will be good if RabbitMQ provides two acknowledgements, one is for that it has been received at client side and second ack is client is completed the processing part.
    Incentivized
    Read full review
    Usability
    Google
    It really saved a lot of time and it's flexibility really can give you infra which is future-proof for most of the use cases may it be streaming or batch data. And with this you can avoid use of resource-heavy big data offerings.
    Incentivized
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    Open Source
    RabbitMQ is very easy to configure for all supported languages (Python, Java, etc.). I have personally used it on Raspberry Pi devices via a Flask Python API as well as in Java applications. I was able to learn it quickly and now have full mastery of it. I highly recommend it for any IoT project.
    Incentivized
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    Support Rating
    Google
    No answers on this topic
    Open Source
    I gave it a 10 but we do not have a support contract with any company for RabbitMQ so there is no official support in that regard. However, there is a community and questions asked on StackOverflow or any other major question and answer site will usually get a response.
    Incentivized
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    Alternatives Considered
    Google
    Google Cloud Dataproc Cloud Datafusion
    Read full review
    Open Source
    RabbitMQ has a few advantages over Azure Service Bus 1) RMQ handles substantially larger files - ASB tops out at 100MB, we use RabbitMQfor files over 200MB 2) RabbitMQ can be easily setup on prem - Azure Service Bus is cloud only 3) RabbitMQ exchanges are easier to configure over ASB subscriptions ASB has a few advantages too 1) Cloud based - just a few mouse clicks and you're up and running
    Incentivized
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    Return on Investment
    Google
    • cost saving from managing our own data center for ETL servers
    • consumption based pricing
    • with auto scaling feature, we were able to expand components to support work load
    Read full review
    Open Source
    • Positive: we don't need to keep way too many backend machines around to deal with bursts because RabbitMQ can absorb and buffer bursts long enough to let an understaffed set of backend services to catch up on processing. Hard to put a number to it but we probably save $5k a month having fewer machines around.
    • Negative: we've got many angry customers due to queues suddenly disappearing and dropping our messages when we try to publish to them afterward. Ideally, RabbitMQ should warn the user when queues expire due to inactivity but it doesn't, and due to our own bugs we've lost a lot of customer data as a result.
    • Positive: makes decoupling the web and API services from the deeper backend services easier by providing queues as an interface. This allowed us to split up our teams and have them develop independently of each other, speeding up software development.
    Incentivized
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