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Apache Pulsar vs Google Cloud Dataflow comparison

 

Comparison Buyer's Guide

Executive Summary

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
18th
Average Rating
8.0
Reviews Sentiment
6.2
Number of Reviews
1
Ranking in other categories
No ranking in other categories
Google Cloud Dataflow
Ranking in Streaming Analytics
7th
Average Rating
8.0
Reviews Sentiment
7.3
Number of Reviews
13
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of April 2025, in the Streaming Analytics category, the mindshare of Apache Pulsar is 2.0%, up from 1.8% compared to the previous year. The mindshare of Google Cloud Dataflow is 7.4%, up from 7.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics
 

Featured Reviews

it_user1087029 - PeerSpot reviewer
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.
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.

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 support team is good and it's easy to use."
"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."
"The solution allows us to program in any language we desire."
"The most valuable features of Google Cloud Dataflow are scalability and connectivity."
"Google Cloud Dataflow is useful for streaming and data pipelines."
"It is a scalable solution."
"The product's installation process is easy...The tool's maintenance part is somewhat easy."
 

Cons

"Documentation is poor because much of it is in Chinese with no English translation."
"Google Cloud Dataflow should include a little cost optimization."
"The solution's setup process could be more accessible."
"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."
"I would like to see improvements in consistency and flexibility for schema design for NoSQL data stored in wide columns."
"There are certain challenges regarding the Google Cloud Composer which can be improved."
"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."
"The deployment time could also be reduced."
"Promoting the technology more broadly would help increase its adoption."
 

Pricing and Cost Advice

Information not available
"Google Cloud Dataflow is a cheap solution."
"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."
"The price of the solution depends on many factors, such as how they pay for tools in the company and its size."
"The tool is cheap."
"The solution is not very expensive."
"The solution is cost-effective."
"Google Cloud is slightly cheaper than AWS."
"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."
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Top Industries

By visitors reading reviews
Computer Software Company
21%
Financial Services Firm
8%
Manufacturing Company
8%
Comms Service Provider
6%
Financial Services Firm
17%
Manufacturing Company
12%
Retailer
11%
Computer Software Company
11%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

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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

No data available
Google Dataflow
 

Overview

 

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: March 2025.
848,716 professionals have used our research since 2012.