AWS Fargate vs Apache Spark comparison

Apache and Amazon Web Services (AWS) are both solutions in the Compute Service category. Apache is ranked #4 with an average rating of 8.7, while Amazon Web Services (AWS) is ranked #3 with an average rating of 8.4. Apache holds a 11.4% mindshare in CS, compared to Amazon Web Services (AWS)’s 15.7% mindshare. Additionally, 90% of Apache users are willing to recommend the solution, compared to 100% of Amazon Web Services (AWS) users who would recommend it.

Apache Spark

Read 64 Apache Spark reviews

1,878 Views
1,439 Comparison Views

90% willing to recommend

AWS Fargate

Read 15 AWS Fargate reviews

4,273 Views
2,555 Comparison Views

100% willing to recommend

Apache Spark

AWS Fargate

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Apache Spark and AWS Fargate based on real PeerSpot user reviews.

Find out in this report how the two Compute Service solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed AWS Fargate vs. Apache Spark Report (Updated: January 2025).

Buyer's Guide

AWS Fargate vs. Apache Spark

January 2025

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Helped 831,158 peers since 2012

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 Spark

Ranking in Compute Service

4th

Average Rating

8.4

Reviews Sentiment

7.7

Number of Reviews

Ranking in other categories

Hadoop (1st), Java Frameworks (2nd)

AWS Fargate

Ranking in Compute Service

3rd

Average Rating

8.6

Reviews Sentiment

7.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of January 2025, in the Compute Service category, the mindshare of Apache Spark is 11.4%, up from 8.2% compared to the previous year. The mindshare of AWS Fargate is 15.7%, down from 15.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Compute Service

Featured Reviews

Ilya Afanasyev

Senior Software Development Engineer at Yahoo!

Reliable, able to expand, and handle large amounts of data well

We use batch processing. It works well with our formats and file versions. There's a lot of functionality. In our pipeline each hour, we make a copy of data from MongoDB, of the changes from MongoDB to some specific file. Each time pipeline copied all of the data, it would do it each time without changes to all of the tables. Tables have a lot of data, and in the last MongoDB version, there is a possibility to read only changed data. This reduced the cost and configuration of the cluster, and we saved about $150,000. The solution is scalable. It's a stable product.

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Subrata Mukherjee

Senior Technical Architect; Head of Platform at Blenheim Chalcot IT Services India

Boost demand response with cost-efficient serverless architecture

We are a venture builder company, and if we select AWS for our product. Our design is based on a serverless architecture model. ECS Fargate is the most convenient way in terms of scalability, integration, and cost control Thanks to the serverless model and easy integration features, a few…

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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 of Apache Spark is its memory processing because it processes data over RAM rather than disk, which is much more efficient and fast."

"The features we find most valuable are the machine learning, data learning, and Spark Analytics."

"The most valuable feature of this solution is its capacity for processing large amounts of data."

"The tool's most valuable feature is its speed and efficiency. It's much faster than other tools and excels in parallel data processing. Unlike tools like Python or JavaScript, which may struggle with parallel processing, it allows us to handle large volumes of data with more power easily."

"Apache Spark can do large volume interactive data analysis."

"Provides a lot of good documentation compared to other solutions."

"I feel the streaming is its best feature."

"The distribution of tasks, like the seamless map-reduce functionality, is quite impressive."

More Apache Spark pros

"Fargate itself is a stable product. We are quite satisfied with its performance."

"If you create your deployment with a good set of rules for how to scale in, you can just set it and forget it."

"All AWS services allow me to manage a wide range of applications and services."

"Fargate is beneficial for hosting our solutions and providing workflow management, creating legal documents, and delivering business intelligence."

"AWS Fargate is an easy-to-use tool to simplify setup. You only pay for the resources you use. If you need to quickly create, delete, or scale applications without managing resources like EC2 instances, Fargate is the best service to use."

"The most valuable feature of AWS Fargate is its ease of use."

"Fargate's integration with other AWS services is really good."

"By using a server's compute resources, one can observe the resource metrics. With AWS, one can determine when servers will be used based on CloudWatch results. For example, CloudWatch informs the application and service platform when the hit ratio has reached the threshold value."

More AWS Fargate pros

Cons

"It's not easy to install."

"We use big data manager but we cannot use it as conditional data so whenever we're trying to fetch the data, it takes a bit of time."

"The logging for the observability platform could be better."

"The migration of data between different versions could be improved."

"It should support more programming languages."

"There could be enhancements in optimization techniques, as there are some limitations in this area that could be addressed to further refine Spark's performance."

"If you have a Spark session in the background, sometimes it's very hard to kill these sessions because of D allocation."

"There were some problems related to the product's compatibility with a few Python libraries."

More Apache Spark cons

"I would like to see enhanced faster application scaling and better integration with the elastic file system to unify storage volumes and improve the launch time of instances."

"If there are any options to manage containers, that would be good. That relates more to the cost point. For example, over the next three months, I'll be making a comparison between solutions like CAST AI and other software-as-a-service platforms that offer Kubernetes management with an emphasis on cost reduction."

"AWS Fargate could improve the privileged mode containers. We had some problems and they were not able to run."

"The main area for improvement is the cost, which could be lowered to be more competitive with other major cloud providers."

"I heard from my team that it's not easy to predict the cost. That is the only issue we have with AWS Fargate, but I think that's acceptable. AWS Fargate isn't user-friendly. Anything related to Software as a Service or microservice architecture is not easy to implement. You're required to have DevOps from your side to implement the solution. AWS Fargate is just a temporary solution for us. When we grow to a certain level, we may use AKS for better control."

"There are features that could be added or enhanced."

"AWS Fargate needs improvement in terms of setup complexity."

"I would like to see the older dashboard instead of the newer version. I don't like the new dashboard."

More AWS Fargate cons

Pricing and Cost Advice

"It is an open-source solution, it is free of charge."

"The solution is affordable and there are no additional licensing costs."

"We are using the free version of the solution."

"Spark is an open-source solution, so there are no licensing costs."

"Apache Spark is an open-source solution, and there is no cost involved in deploying the solution on-premises."

"Apache Spark is an open-source tool."

"It is an open-source platform. We do not pay for its subscription."

"Apache Spark is an expensive solution."

More Apache Spark pricing and cost advice

"I rate the price of AWS Fargate a four out of five."

"We would advise that this solution has a slightly-higher price point than others on the market. There is a free plan available for start-ups, but the free and lower range licensing models do not provide the full functionality."

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Top Industries

By visitors reading reviews

Financial Services Firm

27%

Computer Software Company

13%

Manufacturing Company

University

Financial Services Firm

25%

Computer Software Company

14%

Government

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about Apache Spark?

We use Spark to process data from different data sources.

See all answers

What is your experience regarding pricing and costs for Apache Spark?

Compared to other solutions like Doc DB, Spark is more costly due to the need for extensive infrastructure. It requires significant investment in infrastructure, which can be expensive. While cloud...

See all answers

What needs improvement with Apache Spark?

The main concern is the overhead of Java when distributed processing is not necessary. In such cases, operations can often be done on one node, making Spark's distributed mode unnecessary. Conseque...

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What do you like most about AWS Fargate?

The most valuable feature of Fargate is that it's self-managed. You don't have to configure your own clusters or deploy any Kubernetes clusters. This simplifies the initial deployment and scaling p...

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What needs improvement with AWS Fargate?

There is a tool named Compose that helps in converting the Docker Compose file into a Kubernetes file. For ECS and Fargate, AWS reads a Dockerfile and helps with conversion. However, I am uncertain...

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What advice do you have for others considering AWS Fargate?

I rate Fargate ten out of ten. The most significant advantage is the unified configuration for all containers deployed by ECS, allowing seamless integration with services like OpenAI or Google Gemi...

See all answers

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Compared 41% of the time

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Compared 17% of the time

Heroku vs AWS Fargate

Compared 11% of the time

Oracle Compute Cloud Service vs AWS Fargate

Compared 8% of the time

Apache NiFi vs AWS Fargate

Compared 6% of the time

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Product Reports

Buyer's Guide

Apache Spark

January 2025

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Buyer's Guide

AWS Fargate

January 2025

Download AWS Fargate product report

Learn More

Apache

Amazon Web Services (AWS)

Overview

Spark provides programmers with an application programming interface centered on a data structure called the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. It was developed in response to limitations in the MapReduce cluster computing paradigm, which forces a particular linear dataflowstructure on distributed programs: MapReduce programs read input data from disk, map a function across the data, reduce the results of the map, and store reduction results on disk. Spark's RDDs function as a working set for distributed programs that offers a (deliberately) restricted form of distributed shared memory

A new compute engine that enables you to use containers as a fundamental compute primitive without having to manage the underlying instances. With Fargate, you don’t need to provision, configure, or scale virtual machines in your clusters to run containers. Fargate can be used with Amazon ECS today, with plans to support Amazon Elastic Container Service for Kubernetes (Amazon EKS) in the future.

Fargate has flexible configuration options so you can closely match your application needs and granular, per-second billing.

Sample Customers

NASA JPL, UC Berkeley AMPLab, Amazon, eBay, Yahoo!, UC Santa Cruz, TripAdvisor, Taboola, Agile Lab, Art.com, Baidu, Alibaba Taobao, EURECOM, Hitachi Solutions

Expedia, Intuit, Royal Dutch Shell, Brooks Brothers

Buyer's Guide

AWS Fargate vs. Apache Spark

January 2025

Free Report: AWS Fargate vs. Apache Spark

Find out what your peers are saying about AWS Fargate vs. Apache Spark and other solutions. Updated: January 2025.

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