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 7.6, and holds a 7.9% mindshare in the category. Google is ranked #8 in SA , with an average rating of 7.9, and holds a 8.4% mindshare. Additionally, 90% of Apache users are willing to recommend the solution, compared to 90% of Google users who would recommend it.

Apache NiFi

Read 11 Apache NiFi reviews

2,418 Views
1,132 Comparison Views

90% willing to recommend

Google Cloud Dataflow

Read 10 Google Cloud Dataflow reviews

3,811 Views
3,133 Comparison Views

90% 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, Spot by NetApp and others in Compute Service.

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Buyer's Guide

Compute Service

December 2024

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Categories and Ranking

Apache NiFi

Average Rating

7.8

Number of Reviews

Ranking in other categories

Compute Service (8th)

Google Cloud Dataflow

Average Rating

7.8

Reviews Sentiment

7.3

Number of Reviews

Ranking in other categories

Streaming Analytics (8th)

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 7.9%, up 6.0% compared to last year.
Google Cloud Dataflow, on the other hand, focuses on Streaming Analytics, holds 8.4% mindshare, up 6.8% since last year.

Compute Service

Streaming Analytics

Featured Reviews

Bruno_Silva

Partner at Timestamp, SA

Very easy to schedule jobs that realize improvements and monetize

The use case templates could be more precise to typical business needs. Available templates and model workflows are very high-level so don't really match real needs. It would help to have templates that allow us to see business opportunities. It would help to be able to copy workflow to another device rather than having to ingest it.

Read full review

Tamer Talal

Satellite System Engineer at NARSS

A tool useful for data transmission and data storage that needs to improve its authentication area

The authentication part of the product is an area of concern where improvements are required. For some common users, the solution's authentication part is difficult to use. The scalability of the product is an area of concern where improvements are required. In the future, the product should be made available at a cheaper rate.

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

"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."

"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."

"Visually, this is a good product."

"The initial setup is very 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."

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

More Apache NiFi pros

"It is a scalable solution."

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

"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 most valuable features of Google Cloud Dataflow are the integration, it's very simple if you have the complete stack, which we are using. It is overall very easy to use, user-friendly friendly, and cost-effective if you know how to use it. The solution is very flexible for programmers, if you know how to do scripts or program in Python or any other language, it's extremely easy to use."

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

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

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

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

More Google Cloud Dataflow pros

Cons

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

"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."

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

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

"More features must be added to the product."

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

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

More Apache NiFi cons

"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."

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

"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."

"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."

"The technical support has slight room for improvement."

More Google Cloud Dataflow cons

Pricing and Cost Advice

"The solution is open-source."

"We use the free version of Apache NiFi."

"It's an open-source solution."

"I used the tool's free version."

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

"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."

"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 tool is cheap."

"The solution is not very expensive."

"Google Cloud Dataflow is a cheap solution."

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Top Industries

By visitors reading reviews

Financial Services Firm

19%

Computer Software Company

15%

Manufacturing Company

Retailer

Financial Services Firm

17%

Retailer

12%

Computer Software Company

11%

Manufacturing Company

11%

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?

I used the tool's free version.

See all answers

What needs improvement with Apache NiFi?

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

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?

The solution is not very expensive.

See all answers

What needs improvement with Google Cloud Dataflow?

See all answers

Comparisons

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Compared 25% of the time

Apache Spark vs Apache NiFi

Compared 13% of the time

Azure Stream Analytics vs Apache NiFi

Compared 8% of the time

AWS Fargate vs Apache NiFi

Compared 8% of the time

Apache Storm vs Apache NiFi

Compared 6% of the time

More Apache NiFi Competitors

Databricks vs Google Cloud Dataflow

Compared 42% of the time

Amazon MSK vs Google Cloud Dataflow

Compared 11% of the time

Apache Flink vs Google Cloud Dataflow

Compared 9% of the time

Spring Cloud Data Flow vs Google Cloud Dataflow

Compared 8% of the time

Amazon Kinesis vs Google Cloud Dataflow

Compared 5% of the time

More Google Cloud Dataflow Competitors

Product Reports

Buyer's Guide

Apache NiFi

December 2024

Download Apache NiFi product report

Buyer's Guide

Streaming Analytics

December 2024

Download Google Cloud Dataflow product report

Also Known As

No data available

Google Dataflow

Learn More

Apache

Google

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.

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.

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, Spot by NetApp and others in Compute Service. Updated: December 2024.

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We monitor all Compute Service reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.