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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
Reviews Sentiment
7.0
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

SabinaZeynalova - PeerSpot reviewer
Allows the creation and use of custom functions to achieve desired functionality but limitation in handling monthly transactions due to a lack of partitioning for dates
Apache NiFi is slow to control and needs to be improved. I have to run many jobs and there are already large tables, which can make it difficult to control NiFi on time. There is no one to tell me when there is an incident and my server is down. When we manually start the NiFi process, it is not always started correctly. We can write scripts to run when a message is received from Airflow saying that the firewall is not running. This script will automatically start all servers, including the application servers. It will also check the status of all my NiFi processes and send a callback message with the results. I have written down all the processes that are monitored. 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. In future releases, there are extra features I’d like to add. For example, NiFi is not suitable for migration, and the replication in NiFi is really not good. Because when you process ten years of data, you can't manage all the transactions; it is not enough. Moreover, the handling of monthly transactions is not enough due to a lack of partitioning for dates. And, when we grade a monthly ticket, we must process all data then rerun our ETL jobs. If it's possible, enhancing the partitioning in NiFi for features would be beneficial.
Tamer Talal - PeerSpot reviewer
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.

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 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."
"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 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 is a scalable solution."
"The product's installation process is easy...The tool's maintenance part is somewhat easy."
"The most valuable features of Google Cloud Dataflow are scalability and connectivity."
"The solution allows us to program in any language we desire."
"The service is relatively cheap compared to other batch-processing engines."
"The best feature of Google Cloud Dataflow is its practical connectedness."
"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 support team is good and it's easy to use."
 

Cons

"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."
"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 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."
"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 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."
"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 authentication part of the product is an area of concern where improvements are required."
"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 technical support has slight room for improvement."
"They should do a market survey and then make improvements."
"Google Cloud Dataflow should include a little cost optimization."
"The deployment time could also be reduced."
 

Pricing and Cost Advice

"It's an open-source solution."
"We use the free version of Apache NiFi."
"The solution is open-source."
"I used the tool's free version."
"The tool is cheap."
"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 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 solution is not very expensive."
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Top Industries

By visitors reading reviews
Financial Services Firm
19%
Computer Software Company
15%
Manufacturing Company
8%
Retailer
6%
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 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
 

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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: November 2024.
816,406 professionals have used our research since 2012.