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Apache NiFi 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 NiFi
Average Rating
7.8
Reviews Sentiment
7.4
Number of Reviews
13
Ranking in other categories
Compute Service (8th)
Google Cloud Dataflow
Average Rating
8.0
Reviews Sentiment
7.1
Number of Reviews
14
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
ProductMarket Share (%)
Apache NiFi9.1%
AWS Lambda18.2%
AWS Batch17.2%
Other55.5%
Compute Service
Streaming Analytics Market Share Distribution
ProductMarket Share (%)
Google Cloud Dataflow5.1%
Apache Flink14.8%
Databricks12.5%
Other67.6%
Streaming Analytics
 

Featured Reviews

Bharghava Raghavendra Beesa - PeerSpot reviewer
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.
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

"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."
"We can integrate the tool with other applications easily."
"The most valuable feature has been the range of clients and the range of connectors that we could use."
"The most valuable features of this solution are ease of use and implementation."
"The user interface is good and makes it easy to design very popular workflows."
"It's an automated flow, where you can build a flow from source to destination, then do the transformation in between."
"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."
"It is highly effective for handling real-time data by working with APIs for immediate and continuous data extraction."
"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 best feature of Google Cloud Dataflow is its practical connectedness."
"The solution allows us to program in any language we desire."
"The integration within Google Cloud Platform is very good."
"Google's support team is good at resolving issues, especially with large data."
"It is a scalable solution."
"The product's installation process is easy...The tool's maintenance part is somewhat easy."
"The service is relatively cheap compared to other batch-processing engines."
 

Cons

"I think the UI interface needs to be more user-friendly."
"The quality of JSON data processing could be improved, as JSON workloads require manual conversions without a specific process."
"More features must be added to the product."
"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."
"The use case templates could be more precise to typical business needs."
"The tool should incorporate more tutorials for advanced use cases. It has tutorials for simple use cases."
"There are some claims that NiFi is cloud-native but we have tested it, and it's not."
"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."
"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."
"They should do a market survey and then make improvements."
"There are certain challenges regarding the Google Cloud Composer which can be improved."
"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."
"The solution's setup process could be more accessible."
"Promoting the technology more broadly would help increase its adoption."
"Google Cloud Dataflow should include a little cost optimization."
 

Pricing and Cost Advice

"I used the tool's free version."
"We use the free version of Apache NiFi."
"It's an open-source solution."
"The solution is open-source."
"The solution is not very expensive."
"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."
"The price of the solution depends on many factors, such as how they pay for tools in the company and its size."
"Google Cloud Dataflow is a cheap solution."
"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."
"The solution is cost-effective."
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Top Industries

By visitors reading reviews
Computer Software Company
13%
Manufacturing Company
13%
Financial Services Firm
12%
Retailer
9%
Financial Services Firm
18%
Manufacturing Company
12%
Retailer
11%
Computer Software Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business3
Large Enterprise10
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise2
Large Enterprise10
 

Questions from the Community

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.
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 ...
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?
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...
 

Also Known As

No data available
Google Dataflow
 

Overview

 

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: October 2025.
872,706 professionals have used our research since 2012.