Google Cloud Dataflow vs. IBM MQ

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Google Cloud Dataflow
Score 8.8 out of 10
N/A
Google offers Cloud Dataflow, a managed streaming analytics platform for real-time data insights, fraud detection, and other purposes.N/A
IBM MQ
Score 9.1 out of 10
N/A
IBM MQ (formerly WebSphere MQ and MQSeries) is messaging middleware.N/A
Pricing
Google Cloud DataflowIBM MQ
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Google Cloud DataflowIBM MQ
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Google Cloud DataflowIBM MQ
Features
Google Cloud DataflowIBM MQ
Streaming Analytics
Comparison of Streaming Analytics features of Product A and Product B
Google Cloud Dataflow
7.3
2 Ratings
9% below category average
IBM MQ
-
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 DataflowIBM MQ
Small Businesses
IBM Streams (discontinued)
IBM Streams (discontinued)
Score 9.0 out of 10

No answers on this topic

Medium-sized Companies
Confluent
Confluent
Score 9.3 out of 10
Apache Kafka
Apache Kafka
Score 8.6 out of 10
Enterprises
Spotfire Streaming
Spotfire Streaming
Score 5.2 out of 10
Apache Kafka
Apache Kafka
Score 8.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Google Cloud DataflowIBM MQ
Likelihood to Recommend
8.0
(1 ratings)
8.8
(47 ratings)
Likelihood to Renew
-
(0 ratings)
9.1
(1 ratings)
Usability
-
(0 ratings)
7.8
(6 ratings)
Availability
-
(0 ratings)
9.5
(29 ratings)
Support Rating
-
(0 ratings)
9.1
(27 ratings)
User Testimonials
Google Cloud DataflowIBM MQ
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.
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IBM
In the context of Internet of Things (IoT) applications, IBM MQ plays a pivotal role in managing the substantial data streams emanating from interconnected devices. Its primary function is to guarantee the dependable transmission and processing of data, catering to a diverse range of IoT use cases, including but not limited to smart city initiatives, healthcare monitoring systems, and industrial automation solutions. In the telecommunications sector, IBM MQ is employed for message routing, call detail record (CDR) processing, and network management to ensure real-time data exchange and fault tolerance. When managing the supply chain and logistics, IBM MQ is used to ensure timely and accurate communication between different entities, including suppliers, warehouses, and transportation providers. IBM MQ can be cost-prohibitive for smaller organizations due to licensing and maintenance costs. In such cases, open-source or lightweight messaging solutions may be more appropriate. For scenarios requiring extremely low-latency, real-time data exchange, and high throughput, other messaging technologies, like Apache Kafka, may be more suitable due to their specialized design for such use cases.
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Pros
Google
  • Streaming, Real time work load
  • Batch processing
  • Auto scaling
  • flexible pricing
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IBM
  • The documentation is very clear,It is understandable and the support helps to configure it in the best way.
  • Server guidelines make it possible to get the most out of work management. It's broad, we can work with different operating systems, I really recommend using linux.
  • It is highly compatible with systems, brockers, applications, and data accumulation programs, it is possible to configure everything so that after the installation of programs, they can communicate with each other and then throw data to an external program that accumulates it and represents in clear details of steps to follow and make business decisions.
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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.
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IBM
  • There is limitation on number of svrconn connections you can have to MQ on the mainframe which has been an major issue for us. This has been an issue for us for over 4 years and still no fix although I am aware IBM have been working on a solution over the last year.
  • When upgrading to MQ V9.3 on our MQ appliances there is no fall-back option. This was the same for MQ V9.2 upgrade from MQ V9.0. For production upgrades this I believe is not acceptable.
  • AMS is not supplied as part of the standard mainframe MQ licence. You need an extra licence. IBM tell customers how important security and protecting data is yet they still want to charge for this software. The cost of MQ on the mainframe is not cheap so I would expect AMS to be part of the base product.
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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.
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IBM
I give it a nine because it has significantly improved my team's data reliability and operational efficiency. Its great security features give us peace of mind, knowing our sensitive data is well protected. While the setup might initially be complex, I believe the long-term benefits far outweigh this hurdle.
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Reliability and Availability
Google
No answers on this topic
IBM
The messages are delivered instantly with this software and it integrates with our technology stack, in terms of availability we only had one failure when we were doing some testing and integration with third parties, the features of this software make it always available and its deployment is easy for the company, it does not generate expenses due to failures
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Support Rating
Google
No answers on this topic
IBM
There are very specific things that must be elevated to more specialized areas of support, but the common support is very agile when receiving questions or when we leave concerns in real time. I recommend the support of the program in this regard.
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Alternatives Considered
Google
Google Cloud Dataproc Cloud Datafusion
Read full review
IBM
We found IBM MQ very easy to get started and quick to learn by the new users with a short learning curve and seamlessly integrates with IBM products, and quick to perform self-service analytics and make informed business decisions. IBM MQ is also very straightforward in creating simple and best reports, which are very profitable and productive.
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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
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IBM
  • Positive- Message Reliability and Reduced downtime, increases the ROI many times.
  • Positive- Increased stability and enhanced customer experience
  • Negative- cost is very high - Both licensing and integration cost
  • Negative- Learning and training cost of IBM MQ is high as its complex to use and integrate
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ScreenShots