AWS Batch vs Apache NiFi comparison

Apache and Amazon Web Services (AWS) are both solutions in the Compute Service category. Apache is ranked #7 with an average rating of 7.9, while Amazon Web Services (AWS) is ranked #6 with an average rating of 8.3. Apache holds a 9.5% mindshare in CS, compared to Amazon Web Services (AWS)’s 12.9% mindshare. Additionally, 95% of Apache users are willing to recommend the solution, compared to 100% of Amazon Web Services (AWS) users who would recommend it.

Apache NiFi

Read 22 Apache NiFi reviews

1,725 Views
1,139 Comparison Views

95% willing to recommend

AWS Batch

Read 10 AWS Batch reviews

1,287 Views
1,287 Comparison Views

100% willing to recommend

Apache NiFi

AWS Batch

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Executive SummaryUpdated on May 21, 2025

Apache NiFi and AWS Batch compete in data management and processing. AWS Batch has a slight advantage due to its scalability and integration abilities suited for high compute demands.

Features: Apache NiFi is valued for its flexible data routing, real-time data ingestion, and visual workflow design. It supports numerous integrated endpoints, processors, and connectors, making it ideal for data flow automation without coding. AWS Batch excels in job scheduling, resource provisioning, and massive scalability. It supports containerized workloads with template-driven setup, offering flexibility and ease for compute-intensive jobs.

Room for Improvement: Apache NiFi could benefit from enhanced integration with cloud ecosystems and simplified configuration for complex tasks. Its reliance on Java may limit some real-time processing capabilities. Handling high-volume, low-latency data processes could be refined. AWS Batch can improve by reducing dependencies on AWS-specific services and offering better cost transparency. Enhancements in UI for job management and support for diverse data input types would add value. Users may seek more flexibility in real-time processing similar to other AWS services.

Ease of Deployment and Customer Service: Apache NiFi offers a versatile deployment model with notable customization but may require deeper configuration knowledge. Its integration might be complex for those unfamiliar with the infrastructure. AWS Batch integrates seamlessly with AWS services, simplifying deployment for users with AWS background. It benefits from AWS's robust customer service, catering well to users looking for managed support.

Pricing and ROI: Apache NiFi's open-source nature provides a cost-effective solution with low operational expenses, ideal for businesses with existing infrastructure aiming for strong ROI. In contrast, AWS Batch incurs higher costs due to its reliance on AWS's managed services. However, it provides significant ROI through scalable, efficient resource utilization. AWS Batch's pricing aligns with its advanced features, justifying the cost for data-intensive applications.

To learn more, read our detailed AWS Batch vs. Apache NiFi Report (Updated: December 2025).

Buyer's Guide

AWS Batch vs. Apache NiFi

December 2025

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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

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

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of January 2026, in the Compute Service category, the mindshare of Apache NiFi is 9.5%, up from 7.7% compared to the previous year. The mindshare of AWS Batch is 12.9%, down from 19.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Compute Service Market Share Distribution
Product	Market Share (%)
AWS Batch	12.9%
Apache NiFi	9.5%
Other	77.6%

Compute Service

Featured Reviews

Yamini Vadlamudi

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.

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Ajeet Kumar Singh

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.

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

"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."

"Apache NiFi has positively impacted the organization by making development really easy, allowing efficient design and development, and enabling code reuse which has reduced the development effort."

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

"The user interface is good and makes it easy to design very popular workflows."

"Apache NiFi has positively impacted our organization by making us a lot more productive; I would say development has significantly improved."

"The initial setup is very easy."

"It is highly effective for handling real-time data by working with APIs for immediate and continuous data extraction."

"It's an automated flow, where you can build a flow from source to destination, then do the transformation in between."

More Apache NiFi pros

"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."

"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."

"AWS Batch's deployment was easy."

"The stability of AWS Batch is impeccable; we have run thousands of jobs without encountering any problems, and AWS Batch consistently performs as expected."

"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."

"We can easily integrate AWS container images into the product."

More AWS Batch pros

Cons

"The reason I rate Apache NiFi a seven is that most development folks are afraid to start using Apache NiFi because, to begin with, it does not always directly make sense."

"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."

"Apache NiFi is a very good tool, but there is room for improvement."

"Scalability for Apache NiFi is a problem; it does not scale as well as other Spark solutions."

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

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

More Apache NiFi cons

"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."

"The solution should include better and seamless integration with other AWS services, like Amazon S3 data storage and EC2 compute resources."

"AWS Batch needs to improve its documentation."

"When we run a lot of batch jobs, the UI must show the history."

Pricing and Cost Advice

"I used the tool's free version."

"The solution is open-source."

"We use the free version of Apache NiFi."

"It's an open-source solution."

"AWS Batch's pricing is good."

"The pricing is very fair."

"AWS Batch is a cheap solution."

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Top Industries

By visitors reading reviews

Manufacturing Company

15%

Financial Services Firm

11%

Computer Software Company

11%

University

Financial Services Firm

30%

Manufacturing Company

Computer Software Company

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	5
Midsize Enterprise	1
Large Enterprise	18

By reviewers
Company Size	Count
Small Business	5
Large Enterprise	6

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 ...

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What needs improvement with Apache NiFi?

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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...

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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...

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What do you like most about AWS Batch?

AWS Batch manages the execution of computing workload, including job scheduling, provisioning, and scaling.

See all answers

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.

See all answers

Comparisons

AWS Lambda vs Apache NiFi

Compared 21% of the time

Apache Spark vs Apache NiFi

Compared 16% of the time

Google Cloud Dataflow vs Apache NiFi

Compared 14% of the time

Amazon EC2 vs Apache NiFi

Compared 10% of the time

Azure Stream Analytics vs Apache NiFi

Compared 5% of the time

More Apache NiFi Competitors

AWS Lambda vs AWS Batch

Compared 22% of the time

Apache Spark vs AWS Batch

Compared 20% of the time

Amazon EC2 vs AWS Batch

Compared 15% of the time

AWS Fargate vs AWS Batch

Compared 12% of the time

Amazon EC2 Auto Scaling vs AWS Batch

Compared 6% of the time

More AWS Batch Competitors

Product Reports

Buyer's Guide

Apache NiFi

January 2026

Download Apache NiFi product report

Buyer's Guide

AWS Batch

January 2026

Download AWS Batch product report

Also Known As

No data available

Amazon Batch

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.

Apache

AWS Batch enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. AWS Batch dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted. With AWS Batch, there is no need to install and manage batch computing software or server clusters that you use to run your jobs, allowing you to focus on analyzing results and solving problems. AWS Batch plans, schedules, and executes your batch computing workloads across the full range of AWS compute services and features, such as Amazon EC2 and Spot Instances.

Amazon Web Services (AWS)

Sample Customers

Macquarie Telecom Group, Dovestech, Slovak Telekom, Looker, Hastings Group

Hess, Expedia, Kelloggs, Philips, HyperTrack

Buyer's Guide

AWS Batch vs. Apache NiFi

December 2025

Free Report: AWS Batch vs. Apache NiFi

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