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Apache NiFi vs Google Cloud Dataflow comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Apache NiFi
Average Rating
7.8
Number of Reviews
11
Ranking in other categories
Compute Service (8th)
Google Cloud Dataflow
Average Rating
7.8
Number of Reviews
10
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 8.0%, up 5.9% compared to last year.
Google Cloud Dataflow, on the other hand, focuses on Streaming Analytics, holds 8.3% mindshare, up 6.6% since last year.
Compute Service
Streaming Analytics
 

Featured Reviews

Arjun Pandey - PeerSpot reviewer
Oct 25, 2023
Good monitoring, metrics capabilities and provides ability to design processors with a single click
The good thing about Apache NiFi is that it has a concept called a flow file, and there's something called a flow file processor. The processor is the building block of your entire job. They have close to 500 processors for each purpose. For example, for reading from Kafka, Ni-Fi has a processor called "consumer Kafka". To write to S3, they have a processor called "put S3". Now, if I read from Kafka and write my own application, I'd need to ensure the library I'm using tracks my messages. I'd also need to handle any failures by rereading messages and ensuring acknowledgment. But all this complexity is already handled by Apache processor. They have around 500 processors, with a community investing significant effort into developing them. I can design your processor with a single click, export the entire workflow, and import it. The format is actionable, so NiFi is immediately set up. It's also distributed in nature so that I can scale it across nodes based on the workload. These nodes share their state. If one node goes down during processing, that data might be lost, but any subsequent data is safe. Such occurrences are rare. In essence, if you want a quick solution, Apache NiFi is a strong contender. There are other solutions like AirFlow and some paid pipeline options. AirFlow is open-source but can be complicated. For ETL or ERT solutions, there are pricier options. But if I need a pipeline that I can monitor step by step, Apache NiFi is a good choice. It integrates with Prometheus metrics, allowing me to embed them in my workflow. There's also a processor for integration with Slack, and I can receive notifications when the workflow is completed or fails. Another feature I appreciate is "back pressure," which NiFi handles automatically. It maintains its own queue and addresses back-pressure issues. If, for instance, an upstream entity isn't fast enough, items get stored in a queue, managed internally by NiFi's back pressure algorithm.
Tamer Talal - PeerSpot reviewer
Feb 14, 2024
A tool useful for data transmission and data storage that needs to improve its authentication area
I use the solution in my company for data transmission and data storage One of the good features of the product is the overall capacity that it provides to its users. Though the speed of the product is good, the main feature of the product that I like is its capacity. The authentication part of…

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."
"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 features of this solution are ease of use and implementation."
"The initial setup is very easy."
"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."
"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 best feature of Google Cloud Dataflow is its practical connectedness."
"The most valuable features of Google Cloud Dataflow are scalability and connectivity."
"The support team is good and it's easy to use."
"The product's installation process is easy...The tool's maintenance part is somewhat easy."
"Google Cloud Dataflow is useful for streaming and data pipelines."
"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."
"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."
 

Cons

"More features must be added to the product."
"There should be a better way to integrate a development environment with local tools."
"The use case templates could be more precise to typical business needs."
"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."
"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."
"I think the UI interface needs to be more user-friendly."
"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 deployment time could also be reduced."
"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."
"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 authentication part of the product is an area of concern where improvements are required."
"There are certain challenges regarding the Google Cloud Composer which can be improved."
"The solution's setup process could be more accessible."
"Google Cloud Dataflow should include a little cost optimization."
 

Pricing and Cost Advice

"The solution is open-source."
"I used the tool's free version."
"We use the free version of Apache NiFi."
"It's an open-source solution."
"The solution is not very expensive."
"The price of the solution depends on many factors, such as how they pay for tools in the company and its size."
"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."
"Google Cloud is slightly cheaper than AWS."
"The tool is cheap."
"The solution is cost-effective."
"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
19%
Computer Software Company
16%
Manufacturing Company
8%
Retailer
6%
Financial Services Firm
17%
Computer Software Company
12%
Retailer
12%
Manufacturing Company
11%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What needs improvement with Apache NiFi?
The tool should incorporate more tutorials for advanced use cases. It has tutorials for simple use cases.
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 needs improvement with Google Cloud Dataflow?
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 p...
 

Also Known As

No data available
Google Dataflow
 

Learn More

 

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, Spot by NetApp and others in Compute Service. Updated: October 2024.
814,649 professionals have used our research since 2012.