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AWS Batch vs Apache NiFi comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on May 21, 2025

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
Ranking in Compute Service
7th
Average Rating
7.8
Reviews Sentiment
5.3
Number of Reviews
22
Ranking in other categories
No ranking in other categories
AWS Batch
Ranking in Compute Service
6th
Average Rating
8.4
Reviews Sentiment
7.0
Number of Reviews
10
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of February 2026, in the Compute Service category, the mindshare of Apache NiFi is 9.3%, up from 7.9% compared to the previous year. The mindshare of AWS Batch is 11.6%, down from 20.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Compute Service Market Share Distribution
ProductMarket Share (%)
AWS Batch11.6%
Apache NiFi9.3%
Other79.1%
Compute Service
 

Featured Reviews

YV
architect with 51-200 employees
Unified data flows have simplified large-scale ingestion and have improved SLA reliability
Improvements can be made in the way of the UI. From the deployment perspective, Git configurations are available in 2.6 versions and 2.0 and later versions of Apache NiFi. Before 2.0, templates had to be created and stored in Apache NiFi Registry, which is available. However, templates still need to be imported and exported manually if moving from one environment to another environment. Even in 2.0 versions, although GitHub configurations are available, how it will function needs to be evaluated. Seamless CI/CD deployments are somewhat tricky and challenging when it comes to Apache NiFi with the proper approvals, moving that flow to another environment, and giving the proper RBAC controls. These are areas that could be improved. Documentation is adequate, but the only pain point is the deployment aspect.
AK
Software Engineering Manager – Digital Production Optimization at Yara International ASA
Flexibility in planning and scheduling with containerized workload management has significantly improved computational efficiency
AWS Batch is highly flexible. It allows users to plan, schedule, and compute on containerized workloads. In previous roles, I utilized it for diverse simulations, including on-demand and scheduled computations. It facilitates creating clusters tailored to specific needs, such as memory-centric or CPU-centric workloads, and supports scaling operations massively, like running one hundred thousand Docker containers simultaneously.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The ease of use in Apache NiFi has helped my team because anyone can learn how to use it in a short amount of time, so we were able to get a lot of work done."
"The visual workflow aspect of Apache NiFi is an invaluable feature as it operates on a no-code platform that allows for easy drag-and-drop pipeline construction."
"Speeding up projects with Apache NiFi has helped the organization by resulting in cost savings, and a 30% reduction in cost was noticed as a specific metric regarding those savings."
"Apache NiFi has positively impacted my organization by definitely bridging the gap between the on-premises and cloud interaction until we find a solution to open the firewall for cloud components to directly interact with on-premises services."
"We can integrate the tool with other applications easily."
"Apache NiFi has positively impacted my organization as it continually improves functionality and throughput with each iteration over the past three years."
"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."
"AWS Batch is a cost-effective way to perform batch processing, primarily using spot instances and containers."
"AWS Batch manages the execution of computing workload, including job scheduling, provisioning, and scaling."
"We can easily integrate AWS container images into the product."
"AWS Batch's deployment was easy."
"I appreciate that AWS Batch works with EC2, allowing me to launch jobs and automatically spin up the EC2 instance to run them; when the jobs are completed, the EC2 instance shuts down, making it cost-effective."
"AWS Batch is highly flexible; it allows users to plan, schedule, and compute on containerized workloads, create clusters tailored to specific needs like memory-centric or CPU-centric workloads, and supports scaling operations massively, like running one hundred thousand Docker containers simultaneously."
"There is one other feature in confirmation or call confirmation where you can have templates of what you want to do and just modify those to customize it to your needs. And these templates basically make it a lot easier for you to get started."
"The main feature I like about AWS Batch is its scalability; whether ten extraction jobs or ten thousand jobs are running, it works seamlessly and scales seamlessly."
 

Cons

"The tool should incorporate more tutorials for advanced use cases. It has tutorials for simple use cases."
"There should be a better way to integrate a development environment with local tools."
"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."
"More features must be added to the product."
"Improvements in the user interface to make it easier to use would be beneficial, and adding more security features would make Apache NiFi more secure and robust."
"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."
"I would suggest continuous improvements regarding the custom developer-built processors, as many times the errors that arise are not useful."
"The quality of JSON data processing could be improved, as JSON workloads require manual conversions without a specific process."
"When we run a lot of batch jobs, the UI must show the history."
"AWS Batch needs to improve its documentation."
"The solution should include better and seamless integration with other AWS services, like Amazon S3 data storage and EC2 compute resources."
"The main drawback to using AWS Batch would be the cost. It will be more expensive in some cases than using an HPC. It's more amenable to cases where you have spot requirements."
 

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 pricing is very fair."
"AWS Batch's pricing is good."
"AWS Batch is a cheap solution."
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Top Industries

By visitors reading reviews
Manufacturing Company
15%
Computer Software Company
10%
Financial Services Firm
9%
University
7%
Financial Services Firm
30%
Manufacturing Company
8%
Computer Software Company
7%
Comms Service Provider
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise1
Large Enterprise18
By reviewers
Company SizeCount
Small Business5
Large Enterprise6
 

Questions from the Community

What is your experience regarding pricing and costs for Apache NiFi?
The experience with pricing, setup cost, and licensing was fine, as the integration with the AWS Marketplace was very good. The pricing in Italy is considered a little bit high, but the product is ...
What needs improvement with Apache NiFi?
Improvements can be made in the way of the UI. From the deployment perspective, Git configurations are available in 2.6 versions and 2.0 and later versions of Apache NiFi. Before 2.0, templates had...
What is your primary use case for Apache NiFi?
Apache NiFi is used to fetch data from different sources and ingest it into different destinations. The entire platform depends on Apache NiFi for data transformation and data movement. Multiple so...
Which is better, AWS Lambda or Batch?
AWS Lambda is a serverless solution. It doesn’t require any infrastructure, which allows for cost savings. There is no setup process to deal with, as the entire solution is in the cloud. If you use...
What do you like most about AWS Batch?
AWS Batch manages the execution of computing workload, including job scheduling, provisioning, and scaling.
What is your experience regarding pricing and costs for AWS Batch?
Pricing is good, as AWS Batch allows specifying spot instances, providing cost-effective solutions when launching jobs and spinning up EC2 instances.
 

Comparisons

 

Also Known As

No data available
Amazon Batch
 

Overview

 

Sample Customers

Macquarie Telecom Group, Dovestech, Slovak Telekom, Looker, Hastings Group
Hess, Expedia, Kelloggs, Philips, HyperTrack
Find out what your peers are saying about AWS Batch vs. Apache NiFi and other solutions. Updated: December 2025.
881,665 professionals have used our research since 2012.