Amazon MSK vs Google Cloud Dataflow comparison

Amazon Web Services (AWS) and Google are both solutions in the Streaming Analytics category. Amazon Web Services (AWS) is ranked #6 with an average rating of 7.4, while Google is ranked #8 with an average rating of 7.9. Amazon Web Services (AWS) holds a 8.2% mindshare in SA, compared to Google’s 7.7% mindshare. Additionally, 90% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 91% of Google users who would recommend it.

Amazon MSK

Read 10 Amazon MSK reviews

4,814 Views
3,718 Comparison Views

90% willing to recommend

Google Cloud Dataflow

Read 11 Google Cloud Dataflow reviews

3,450 Views
2,838 Comparison Views

91% willing to recommend

Amazon MSK

Google Cloud Dataflow

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 17, 2024

Google Cloud Dataflow and Amazon MSK compete in data processing and streaming solutions. Google Cloud Dataflow is noted for high scalability and ease of use, while Amazon MSK is recognized for robust real-time streaming features and reliability.

Features: Google Cloud Dataflow integrates smoothly with Google services, offers excellent scalability, and supports complex data processing. Amazon MSK provides real-time Kafka streaming, integrates easily with AWS services, and ensures strong security.

Room for Improvement: Google Cloud Dataflow could improve its real-time streaming capabilities and offer more granular control settings. Amazon MSK could enhance user-friendliness for non-AWS users and provide more straightforward deployment options. Both could benefit from additional third-party integrations.

Ease of Deployment and Customer Service: Google Cloud Dataflow is known for easy deployment within the Google Cloud ecosystem and responsive customer support. Amazon MSK offers detailed configuration options and a reliable support network, focusing on more controlled setups.

Pricing and ROI: Google Cloud Dataflow's transparent pricing allows flexible cost management, yielding strong ROI. Amazon MSK, while having higher initial costs, offers substantial ROI via efficient real-time data streaming. Dataflow's cost-effectiveness contrasts with MSK's investment in real-time streaming capabilities.

To learn more, read our detailed Amazon MSK vs. Google Cloud Dataflow Report (Updated: January 2025).

Buyer's Guide

Amazon MSK vs. Google Cloud Dataflow

January 2025

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

Amazon MSK

Ranking in Streaming Analytics

6th

Average Rating

7.4

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Google Cloud Dataflow

Ranking in Streaming Analytics

8th

Average Rating

8.0

Reviews Sentiment

7.3

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of February 2025, in the Streaming Analytics category, the mindshare of Amazon MSK is 8.2%, down from 9.5% compared to the previous year. The mindshare of Google Cloud Dataflow is 7.7%, up from 6.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics

Featured Reviews

FNU AKSHANSH

Senior Data Engineer at a computer software company with 201-500 employees

Streamlines our processes, and we don't need to configure any VPCs; it's automatic

We don't have many use cases involving ingesting large amounts of data and scaling up and down. We have a clear understanding of our data volume, which remains relatively constant throughout the week. While we're aware of other features Amazon MSK offers, we feel confident in our current setup. If our requirements change significantly in the future, we'll reassess our needs and consider adopting Amazon MSK.

Read full review

Jana Polianskaja

Data Engineer at Accenture

Build Scalable Data Pipelines with Apache Beam and Google Cloud Dataflow

As a data engineer, I find several features of Google Cloud Dataflow particularly valuable. The ability to test solutions locally using Direct Runner is crucial for development, allowing me to validate pipelines without incurring the costs of full Dataflow jobs. The unified programming model for both batch and streaming processing is exceptional - requiring only minor code adjustments to optimize for either mode. This flexibility extends to language support, with robust implementations in both Java and Python, allowing teams to leverage their existing expertise. The platform's comprehensive monitoring capabilities are another standout feature. The intuitive interface, Grafana integration, and extensive service connectivity make troubleshooting and performance tracking highly efficient. Furthermore, seamless integration with Google Cloud Composer (managed Airflow) enables sophisticated orchestration of data pipelines.

Read full review

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"It is a stable product."

"Amazon MSK has good integration because our team has been undergoing significant changes. Coupling it with MSK within AWS is helpful. We don't have to set up additionals or monitor external environments. This"

"Amazon MSK has significantly improved our organization by building seamless integration between systems."

"Amazon MSK's separation of concerns and ease of creating and deploying new features are highly valuable. It just requires to assign them to the topic, and then anyone who needs to consume these messages can do so directly from Amazon MSK. This separation of concerns makes it very convenient, especially for new feature development, as developers can easily access the messages they need without having to deal with complex server communications or protocol setups."

"The solution's technical support was helpful."

"It offers good stability."

"The most valuable feature of Amazon MSK is the integration."

"Amazon MSK's scalability is very good."

More Amazon MSK pros

"The best feature of Google Cloud Dataflow is its practical connectedness."

"The most valuable features of Google Cloud Dataflow are scalability and connectivity."

"The service is relatively cheap compared to other batch-processing engines."

"It allows me to test solutions locally using runners like Direct Runner without having to start a Dataflow job, which can be costly."

"I don't need a server running all the time while using the tool. It is also easy to setup. The product offers a pay-as-you-go service."

"It is a scalable solution."

"Google Cloud Dataflow is useful for streaming and data pipelines."

"I would rate the overall solution a ten out of ten."

More Google Cloud Dataflow pros

Cons

"One of the reasons why we prefer Kafka is because the support is a little bit difficult to manage with Amazon MSK."

"The configuration seems a little complex and the documentation on the product is not available."

"It should be more flexible, integration-wise."

"It does not autoscale. Because if you do keep it manually when you add a note to the cluster and then you register it, then it is scalable, but the fact that you have to go and do it, I think, makes it, again, a bit of some operational overhead when managing the cluster."

"It would be really helpful if Amazon MSK could provide a single installation that covers all the servers."

"The product's schema support needs enhancement. It will help enhance integration with many kinds of languages of programming languages, especially for environments using languages like .NET."

"Horizontal scale-out is actually not easy, making it an area where improvements are required."

"Amazon MSK could improve on the features they offer. They are still lagging behind Confluence."

More Amazon MSK cons

"The authentication part of the product is an area of concern where improvements are required."

"The deployment time could also be reduced."

"They should do a market survey and then make improvements."

"Google Cloud Dataflow should include a little cost optimization."

"When I deploy the product in local errors, a lot of errors pop up which are not always caught. The solution's error logging is bad. It can take a lot of time to debug the errors. It needs to have better logs."

"Google Cloud Data Flow can improve by having full simple integration with Kafka topics. It's not that complicated, but it could improve a bit. The UI is easy to use but the experience could be better. There are other tools available that do a better job."

"I would like Google Cloud Dataflow to be integrated with IT data flow and other related services to make it easier to use as it is a complex tool."

"Promoting the technology more broadly would help increase its adoption."

More Google Cloud Dataflow cons

Pricing and Cost Advice

"The platform has better pricing than one of its competitors."

"When you create a complete enterprise-driven architecture that is deployable on an enterprise scale, I would say that the prices of Amazon MSK and Confluent Platform become comparable."

"The price of Amazon MSK is less than some competitor solutions, such as Confluence."

"The price of the solution depends on many factors, such as how they pay for tools in the company and its size."

"On a scale from one to ten, where one is cheap, and ten is expensive, I rate Google Cloud Dataflow's pricing a four out of ten."

"The solution is not very expensive."

"The solution is cost-effective."

"The tool is cheap."

"Google Cloud Dataflow is a cheap solution."

"Google Cloud is slightly cheaper than AWS."

"On a scale from one to ten, where one is cheap, and ten is expensive, I rate the solution's pricing a seven to eight out of ten."

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Top Industries

By visitors reading reviews

Financial Services Firm

23%

Computer Software Company

19%

Manufacturing Company

Retailer

Financial Services Firm

17%

Manufacturing Company

12%

Retailer

12%

Computer Software Company

12%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about Amazon MSK?

Amazon MSK has significantly improved our organization by building seamless integration between systems.

See all answers

What needs improvement with Amazon MSK?

From AWS, I would consider more MSK schema validation is needed. It is easy to integrate if you have an application, but on-topic integration is more complex. You can do it with EvenBridge very eas...

See all answers

What is your primary use case for Amazon MSK?

I have used Confluent Cloud and Amazon MSK in my company. We are not using it for analytics and it is more for CDC processes, so we change the capture processes. It is used to extract data from a d...

See all answers

What do you like most about Google Cloud Dataflow?

The product's installation process is easy...The tool's maintenance part is somewhat easy.

See all answers

What is your experience regarding pricing and costs for Google Cloud Dataflow?

Google Cloud Dataflow costs are primarily driven by compute resources (worker type and count) and data volume. However, other factors like pipeline complexity also contribute significantly to the t...

See all answers

What needs improvement with Google Cloud Dataflow?

Apache Beam represents a powerful data processing solution that deserves wider recognition in the broader tech community. This technology offers remarkable capabilities for handling data at scale, ...

See all answers

Comparisons

Azure Stream Analytics vs Amazon MSK

Compared 31% of the time

Confluent vs Amazon MSK

Compared 23% of the time

Amazon Kinesis vs Amazon MSK

Compared 14% of the time

Apache Flink vs Amazon MSK

Compared 7% of the time

Aiven Platform vs Amazon MSK

Compared 4% of the time

More Amazon MSK Competitors

Databricks vs Google Cloud Dataflow

Compared 42% of the time

Apache NiFi vs Google Cloud Dataflow

Compared 12% of the time

Apache Flink vs Google Cloud Dataflow

Compared 11% of the time

Spring Cloud Data Flow vs Google Cloud Dataflow

Compared 8% of the time

Amazon Kinesis vs Google Cloud Dataflow

Compared 5% of the time

More Google Cloud Dataflow Competitors

Product Reports

Buyer's Guide

Amazon MSK

February 2025

Download Amazon MSK product report

Buyer's Guide

Streaming Analytics

January 2025

Download Google Cloud Dataflow product report

Also Known As

Amazon Managed Streaming for Apache Kafka

Google Dataflow

Overview

Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed service that enables you to build and run applications that use Apache Kafka to process streaming data. Amazon MSK provides the control-plane operations, such as those for creating, updating, and deleting clusters.

Amazon Web Services (AWS)

Google Dataflow is a unified programming model and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. Cloud Dataflow frees you from operational tasks like resource management and performance optimization.

Google

Sample Customers

Expedia, Intuit, Royal Dutch Shell, Brooks Brothers

Absolutdata, Backflip Studios, Bluecore, Claritics, Crystalloids, Energyworx, GenieConnect, Leanplum, Nomanini, Redbus, Streak, TabTale

Buyer's Guide

Amazon MSK vs. Google Cloud Dataflow

January 2025

Free Report: Amazon MSK vs. Google Cloud Dataflow

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