Apache Pulsar vs Google Cloud Dataflow comparison

Pulsar and Google are both solutions in the Streaming Analytics category. Pulsar is ranked #20, while Google is ranked #13 with an average rating of 8.5. Pulsar holds a 2.8% mindshare in SA, compared to Google’s 3.9% mindshare. Additionally, 100% of Pulsar users are willing to recommend the solution, compared to 93% of Google users who would recommend it.

Apache Pulsar

Read 1 Apache Pulsar review

815 Views
815 Comparison Views

100% willing to recommend

Google Cloud Dataflow

Read 14 Google Cloud Dataflow reviews

2,258 Views
1,919 Comparison Views

93% willing to recommend

Apache Pulsar

Google Cloud Dataflow

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Apache Pulsar and Google Cloud Dataflow based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Microsoft and others in Streaming Analytics.

To learn more, read our detailed Streaming Analytics Report (Updated: February 2026).

Buyer's Guide

Streaming Analytics

February 2026

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Helped 884,873 peers since 2012

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

Apache Pulsar

Ranking in Streaming Analytics

20th

Average Rating

8.0

Reviews Sentiment

6.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Google Cloud Dataflow

Ranking in Streaming Analytics

13th

Average Rating

8.0

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of March 2026, in the Streaming Analytics category, the mindshare of Apache Pulsar is 2.8%, up from 2.0% compared to the previous year. The mindshare of Google Cloud Dataflow is 3.9%, down from 7.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Mindshare Distribution
Product	Mindshare (%)
Google Cloud Dataflow	3.9%
Apache Pulsar	2.8%
Other	93.3%

Streaming Analytics

Featured Reviews

it_user1087029

Solution Architect at Vlaanderen connect.

The solution can mimic other APIs without changing a line of code

The solution operates as a classic message broker but also as a streaming platform. It operates differently than a traditional streaming platform with storage and computing handled separately. It scales easier and better than Kafka which can be stubborn. You can even make it act like Kafka because it understands Kafka APIs. There are even companies that will sell you Kafka but underneath it is Apache Pulsar. The solution is very compatible because it can mimic other APIs without changing a line of code.

Read full review

Preethi Reddy

Senior Data Engineer at Accruent

Enables real-time insights and efficient data preparation for machine learning

Google Cloud Dataflow's features for event stream processing allow us to gain various insights like detecting real-time alerts. For integration, we use Dataflow to extract data from different sources like APIs and flat files. We then perform data cleansing, including deduplications, schema standardizations, and filtering of invalid records. We also use it for preparing data for machine learning models, transforming data, and accelerating models.

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

"The solution operates as a classic message broker but also as a streaming platform."

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

"The solution allows us to program in any language we desire."

"Google's support team is good at resolving issues, especially with large data."

"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."

"The support team is good and it's easy to use."

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

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

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

More Google Cloud Dataflow pros

Cons

"Documentation is poor because much of it is in Chinese with no English translation."

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

"I would like to see improvements in consistency and flexibility for schema design for NoSQL data stored in wide columns."

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

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

"There are certain challenges regarding the Google Cloud Composer which can be improved."

"The technical support has slight room for improvement."

"The deployment time could also be reduced."

"The system could function in an automated fashion and provide suggestions based on past transactions to achieve better scalability."

More Google Cloud Dataflow cons

Pricing and Cost Advice

Information not available

"The solution is cost-effective."

"The solution is not very expensive."

"Google Cloud Dataflow is a cheap solution."

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

"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."

"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 tool is cheap."

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Top Industries

By visitors reading reviews

Financial Services Firm

16%

Comms Service Provider

Government

Insurance Company

Financial Services Firm

17%

Manufacturing Company

13%

Retailer

11%

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	2
Large Enterprise	10

Questions from the Community

Ask a question

Earn 20 points

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.

See all answers

What needs improvement with Google Cloud Dataflow?

It can be improved in several ways. The system could function in an automated fashion and provide suggestions based on past transactions to achieve better scalability. Implementing AI-based suggest...

See all answers

What is your primary use case for Google Cloud Dataflow?

It is used for exporting data, such as customer clicks, customer interactions with emails, and link tracking. The Google Analytics streaming data is used to establish customer behavioral patterns.

See all answers

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Compared 8% of the time

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Compared 7% of the time

Azure Stream Analytics vs Google Cloud Dataflow

Compared 6% of the time

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Product Reports

Buyer's Guide

Streaming Analytics

February 2026

Download Apache Pulsar product report

Buyer's Guide

Google Cloud Dataflow

March 2026

Download Google Cloud Dataflow product report

Also Known As

No data available

Google Dataflow

Overview

Apache Pulsar is a cloud-native, distributed messaging and streaming platform originally created at Yahoo! and now a top-level Apache Software Foundation project

Pulsar

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

Information Not Available

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

Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Microsoft and others in Streaming Analytics. Updated: February 2026.

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