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Azure Stream Analytics vs Google Cloud Dataflow comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 17, 2024

Review summaries and opinions

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

ROI

Sentiment score
6.1
Azure Stream Analytics offers quick, cost-effective deployment, resulting in positive ROI and customer satisfaction for non-complex scenarios.
Sentiment score
5.6
Google Cloud Dataflow was appreciated for cost savings and time efficiency, though some considered its impact not fully assessable yet.
 

Customer Service

Sentiment score
6.5
Azure Stream Analytics support is effective and responsive, with service quality varying by subscription and occasional communication challenges.
Sentiment score
6.6
Google Cloud Dataflow support varies, with users praising technical resolution but highlighting inconsistent response times and accessibility.
The support on critical issues depends on the level of subscription that you have with Microsoft itself.
They've managed to answer all my questions and provide help in a timely manner.
There is a big communication gap due to lack of understanding of local scenarios and language barriers.
The fact that no interaction is needed shows their great support since I don't face issues.
Google's support team is good at resolving issues, especially with large data.
Whenever we have issues, we can consult with Google.
 

Scalability Issues

Sentiment score
7.5
Azure Stream Analytics is highly scalable, cloud-based, easily integrated, adaptable, and efficiently manages varying workloads, despite some cost concerns.
Sentiment score
7.3
Google Cloud Dataflow excels in scalability and efficiency, making it ideal for real-time data processing and dynamic needs.
Maintenance requires a couple of people, however, it's not a full-time endeavor.
Azure Stream Analytics is scalable, and I would rate it seven out of ten.
Google Cloud Dataflow can handle large data processing for real-time streaming workloads as they grow, making it a good fit for our business.
As a team lead, I'm responsible for handling five to six applications, but Google Cloud Dataflow seems to handle our use case effectively.
Google Cloud Dataflow has auto-scaling capabilities, allowing me to add different machine types based on pace and requirements.
 

Stability Issues

Sentiment score
6.5
Azure Stream Analytics is reliable but can face downtime, bugs, transformation challenges, and requires tuning for optimal stability.
Sentiment score
8.3
Google Cloud Dataflow is stable, reliably handles tasks, and benefits from automatic scaling, with minor issues on complex tasks.
They require significant effort and fine-tuning to function effectively.
I have not encountered any issues with the performance of Dataflow, as it is stable and backed by Google services.
The job we built has not failed once over six to seven months.
The automatic scaling feature helps maintain stability.
 

Room For Improvement

Azure Stream Analytics needs better pricing, logging, customization, connectivity, integration, UI, flexibility, support, error handling, and simplified licensing.
Google Cloud Dataflow needs better Kafka integration, improved error logs, reduced startup time, and enhanced Python SDK features.
A cost comparison between products is also not straightforward.
There's setup time required to get it integrated with different services such as Power BI, so it's not a straight out-of-the-box configuration.
Although customers can invite Microsoft Taiwan office staff for introductions, there are not many useful case references, suggesting room for improvement in market support.
Outside of Google Cloud Platform, it is problematic for others to use it and may require promotion as an actual technology.
I would like to see improvements in consistency and flexibility for schema design for NoSQL data stored in wide columns.
Dealing with a huge volume of data causes failure due to array size.
 

Setup Cost

Azure Stream Analytics offers competitive pricing but can be costly for enterprises; users find billing reports confusing.
Google Cloud Dataflow is praised for cost-effectiveness and scalability, offering competitive pricing influenced by pipeline complexity and company size.
The Azure solution is better now, and competitors, even within Microsoft, may offer solutions that could make it cheaper.
Regarding the cost of Azure Stream Analytics, I believe the price is reasonable for the tool.
We sell the data analytics value and operational value to customers, focusing on productivity and efficiency from the cloud.
It is part of a package received from Google, and they are not charging us too high.
 

Valuable Features

Azure Stream Analytics provides integrated, scalable real-time analytics with SQL queries and machine learning, enhancing data processing capabilities efficiently.
Google Cloud Dataflow offers seamless integration, multi-language support, scalability, and serverless data handling for efficient batch and streaming processes.
It's very accurate and uses existing technologies in terms of writing queries, utilizing standard query languages such as SQL, Spark, and others to provide information.
Clients can choose and subscribe to the service items they need, making it more flexible than IBM solutions, especially in data analytics or data governance.
It is quite easy for my technicians to understand, and the learning curve is not steep.
It supports multiple programming languages such as Java and Python, enabling flexibility without the need to learn something new.
We then perform data cleansing, including deduplications, schema standardizations, and filtering of invalid records.
The integration within Google Cloud Platform is very good.
 

Categories and Ranking

Azure Stream Analytics
Ranking in Streaming Analytics
4th
Average Rating
7.8
Reviews Sentiment
6.7
Number of Reviews
28
Ranking in other categories
No ranking in other categories
Google Cloud Dataflow
Ranking in Streaming Analytics
7th
Average Rating
8.0
Reviews Sentiment
7.1
Number of Reviews
14
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2025, in the Streaming Analytics category, the mindshare of Azure Stream Analytics is 8.8%, down from 12.5% compared to the previous year. The mindshare of Google Cloud Dataflow is 6.0%, down from 7.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics
 

Featured Reviews

SantiagoCordero - PeerSpot reviewer
Native connectors and integration simplify tasks but portfolio complexity needs addressing
There are too many products in the Azure landscape, which sometimes leads to overlap between them. Microsoft continuously releases new products or solutions, which can be frustrating when determining the appropriate features from one solution over another. A cost comparison between products is also not straightforward. They should simplify their portfolio. The Microsoft licensing system is confusing and not easy to understand, and this is something they should address. In the future, I may stop using Stream Analytics and move to other solutions. I discussed Palantir earlier, which is something I want to explore in depth because it allows me to accomplish more efficiently compared to solely using Azure. Additionally, the vendors should make the solution more user-friendly, incorporating low-code and no-code features. This is something I wish to explore further.
Jana Polianskaja - PeerSpot reviewer
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.
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Computer Software Company
14%
Manufacturing Company
9%
Retailer
7%
Financial Services Firm
17%
Manufacturing Company
12%
Retailer
11%
Computer Software Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

Which would you choose - Databricks or Azure Stream Analytics?
Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their orga...
What is your experience regarding pricing and costs for Azure Stream Analytics?
The solution does not need any license; it comes with your subscription.
What needs improvement with Azure Stream Analytics?
It does not always give you the right reason or the correct reason. For example, if a service is stopped, it just tells you that it stopped and started. It does not give you any good insight as to ...
What do you like most about Google Cloud Dataflow?
The product's installation process is easy...The tool's maintenance part is somewhat easy.
What is your experience regarding pricing and costs for Google Cloud Dataflow?
Pricing is normal. It is part of a package received from Google, and they are not charging us too high.
What needs improvement with Google Cloud Dataflow?
I am not sure, as we built only one job, and it is running on a daily basis. Everything else is managed using BigQuery schedulers and Talend. However, occasionally, dealing with a huge volume of da...
 

Also Known As

ASA
Google Dataflow
 

Overview

 

Sample Customers

Rockwell Automation, Milliman, Honeywell Building Solutions, Arcoflex Automation Solutions, Real Madrid C.F., Aerocrine, Ziosk, Tacoma Public Schools, P97 Networks
Absolutdata, Backflip Studios, Bluecore, Claritics, Crystalloids, Energyworx, GenieConnect, Leanplum, Nomanini, Redbus, Streak, TabTale
Find out what your peers are saying about Azure Stream Analytics vs. Google Cloud Dataflow and other solutions. Updated: July 2025.
865,164 professionals have used our research since 2012.