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 7.7, and holds a 8.9% mindshare in the category. Google is ranked #7 in SA , with an average rating of 8.1, and holds a 6.5% mindshare. Additionally, 92% of Apache users are willing to recommend the solution, compared to 92% of Google users who would recommend it.

Apache NiFi

Read 13 Apache NiFi reviews

2,408 Views
1,421 Comparison Views

92% willing to recommend

Google Cloud Dataflow

Read 13 Google Cloud Dataflow reviews

3,102 Views
2,544 Comparison Views

92% 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.

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Buyer's Guide

Compute Service

July 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

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

7.3

Number of Reviews

Ranking in other categories

Streaming Analytics (7th)

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 8.9%, up 7.7% compared to last year.
Google Cloud Dataflow, on the other hand, focuses on Streaming Analytics, holds 6.5% mindshare, down 7.5% since last year.

Compute Service

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

"The user interface is good and makes it easy to design very popular workflows."

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

"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."

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

"The most valuable features of this solution are ease of use and implementation."

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

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

"The initial setup is very easy."

More Apache NiFi pros

"The integration within Google Cloud Platform is very good."

"It is a scalable solution."

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

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

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

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

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

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

More Google Cloud Dataflow pros

Cons

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

"The use case templates could be more precise to typical business needs."

"There should be a better way to integrate a development environment with local tools."

"More features must be added to the product."

"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."

"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."

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

More Apache NiFi cons

"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."

"The solution's setup process could be more accessible."

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

"The technical support has slight room for improvement."

"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."

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

More Google Cloud Dataflow cons

Pricing and Cost Advice

"We use the free version of Apache NiFi."

"It's an open-source solution."

"The solution is open-source."

"I used the tool's free version."

"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 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."

"The tool is cheap."

"The solution is cost-effective."

"Google Cloud is slightly cheaper than AWS."

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

15%

Computer Software Company

13%

Manufacturing Company

10%

Retailer

Financial Services Firm

18%

Manufacturing Company

12%

Retailer

11%

Computer Software Company

10%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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?

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...

See all answers

Comparisons

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Compared 28% of the time

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AWS Fargate vs Apache NiFi

Compared 10% of the time

Apache Storm vs Apache NiFi

Compared 7% of the time

Azure Stream Analytics vs Apache NiFi

Compared 7% of the time

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Databricks vs Google Cloud Dataflow

Compared 36% of the time

Apache Flink vs Google Cloud Dataflow

Compared 16% of the time

Spring Cloud Data Flow vs Google Cloud Dataflow

Compared 7% of the time

Amazon MSK vs Google Cloud Dataflow

Compared 7% of the time

Amazon Kinesis vs Google Cloud Dataflow

Compared 4% of the time

More Google Cloud Dataflow Competitors

Product Reports

Buyer's Guide

Apache NiFi

July 2025

Download Apache NiFi product report

Buyer's Guide

Google Cloud Dataflow

July 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, Oracle and others in Compute Service. Updated: July 2025.

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