Apache NiFi vs Google Cloud Dataflow comparison

The compared Apache and Google solutions aren't in the same category. Apache is ranked #8 in CS , with an average rating of 7.8, and holds a 9.1% mindshare in the category. Google is ranked #9 in SA , with an average rating of 8.1, and holds a 5.1% mindshare. Additionally, 92% of Apache users are willing to recommend the solution, compared to 93% of Google users who would recommend it.

Apache NiFi

Read 13 Apache NiFi reviews

1,814 Views
1,125 Comparison Views

92% willing to recommend

Google Cloud Dataflow

Read 14 Google Cloud Dataflow reviews

2,451 Views
2,034 Comparison Views

93% willing to recommend

Apache NiFi

Google Cloud Dataflow

Comparison Buyer's Guide

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Executive Summary

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

Find out what your peers are saying about Amazon Web Services (AWS), Apache, Zadara and others in Compute Service.

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Buyer's Guide

Compute Service

September 2025

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Helped 868,759 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 NiFi

Average Rating

7.8

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

Compute Service (8th)

Google Cloud Dataflow

Average Rating

8.0

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

Streaming Analytics (9th)

Mindshare comparison

Apache NiFi and Google Cloud Dataflow aren’t in the same category and serve different purposes. Apache NiFi is designed for Compute Service and holds a mindshare of 9.1%, up 8.0% compared to last year.
Google Cloud Dataflow, on the other hand, focuses on Streaming Analytics, holds 5.1% mindshare, down 7.8% since last year.

Compute Service Market Share Distribution
Product	Market Share (%)
Apache NiFi	9.1%
AWS Lambda	18.2%
AWS Batch	17.2%
Other	55.5%

Compute Service

Streaming Analytics Market Share Distribution
Product	Market Share (%)
Google Cloud Dataflow	5.1%
Apache Flink	14.8%
Databricks	12.5%
Other	67.6%

Streaming Analytics

Featured Reviews

Bharghava Raghavendra Beesa

Senior Developer at Infosys

The tool enables effective data transformation and integration

There are some areas for improvement, particularly with record-level tasks that take a bit of time. The quality of JSON data processing could be improved, as JSON workloads require manual conversions without a specific process. Enhancing features related to alerting would be helpful, including mobile alerts for pipeline issues. Integration with mobile devices for error alerts would simplify information delivery.

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's an automated flow, where you can build a flow from source to destination, then do the transformation in between."

"The most valuable feature has been the range of clients and the range of connectors that we could use."

"It is highly effective for handling real-time data by working with APIs for immediate and continuous data extraction."

"Visually, this is a good product."

"The initial setup is very easy."

"We can integrate the tool with other applications easily."

"The initial setup is very easy. I would rate my experience with the initial setup a ten out of ten, where one point is difficult, and ten points are easy."

"Apache NiFi is user-friendly. Its most valuable features for handling large volumes of data include its multitude of integrated endpoints and clients and the ability to create cron jobs to run tasks at regular intervals."

More Apache NiFi pros

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

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

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

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

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

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

More Google Cloud Dataflow pros

Cons

"The tool should incorporate more tutorials for advanced use cases. It has tutorials for simple use cases."

"The quality of JSON data processing could be improved, as JSON workloads require manual conversions without a specific process."

"There is room for improvement in integration with SSO. For example, NiFi does not have any integration with SSO. And if I want to give some kind of rollback access control across the organization. That is not possible."

"We run many jobs, and there are already large tables. When we do not control NiFi on time, all reports fail for the day. So it's pretty slow to control, and it has to be improved."

"More features must be added to the product."

"There are some claims that NiFi is cloud-native but we have tested it, and it's not."

"I think the UI interface needs to be more user-friendly."

"The overall stability of this solution could be improved. In a future release, we would like to have access to more features that could be used in a parallel way. This would provide more freedom with processing."

More Apache NiFi cons

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

"The deployment time could also be reduced."

"Occasionally, dealing with a huge volume of data causes failure due to array size."

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

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

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

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

"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."

More Google Cloud Dataflow cons

Pricing and Cost Advice

"It's an open-source solution."

"The solution is open-source."

"We use the free version of Apache NiFi."

"I used the tool's free version."

"The solution is cost-effective."

"The solution is not very expensive."

"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."

"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."

"Google Cloud is slightly cheaper than AWS."

"Google Cloud Dataflow is a cheap solution."

"The tool is cheap."

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

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Top Industries

By visitors reading reviews

Computer Software Company

15%

Financial Services Firm

12%

Manufacturing Company

12%

Retailer

Financial Services Firm

17%

Manufacturing Company

11%

Retailer

11%

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	3
Large Enterprise	10

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

Questions from the Community

What do you like most about Apache NiFi?

The initial setup is very easy.

See all answers

What is your experience regarding pricing and costs for Apache NiFi?

Apache NiFi is open-source and free. Its integration with systems like Cloudera can be expensive, but Apache NiFi itself presents the best pricing as a standalone tool.

See all answers

What needs improvement with Apache NiFi?

The logging system of Apache NiFi needs improvement. It is difficult to debug compared to Airflow ( /products/apache-airflow-reviews ), where task details and issues are clear. With Apache NiFi, I ...

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?

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

Comparisons

AWS Lambda vs Apache NiFi

Compared 26% of the time

Apache Spark vs Apache NiFi

Compared 18% of the time

Amazon EC2 vs Apache NiFi

Compared 9% of the time

Apache Storm vs Apache NiFi

Compared 8% of the time

AWS Fargate vs Apache NiFi

Compared 7% of the time

More Apache NiFi Competitors

Databricks vs Google Cloud Dataflow

Compared 35% of the time

Apache Flink vs Google Cloud Dataflow

Compared 23% of the time

Spring Cloud Data Flow vs Google Cloud Dataflow

Compared 7% of the time

Amazon MSK vs Google Cloud Dataflow

Compared 5% of the time

AWS Lambda vs Google Cloud Dataflow

Compared 4% of the time

More Google Cloud Dataflow Competitors

Product Reports

Buyer's Guide

Apache NiFi

September 2025

Download Apache NiFi product report

Buyer's Guide

Google Cloud Dataflow

September 2025

Download Google Cloud Dataflow product report

Also Known As

No data available

Google Dataflow

Overview

Apache NiFi is an easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.

Apache

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

Macquarie Telecom Group, Dovestech, Slovak Telekom, Looker, Hastings Group

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

Find out what your peers are saying about Amazon Web Services (AWS), Apache, Zadara and others in Compute Service. Updated: September 2025.

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