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AWS Fargate vs Apache Spark 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:
 

ROI

Sentiment score
7.3
Apache Spark reduces operational costs by up to 50%, offering high ROI and efficient performance despite infrastructure expenses.
Sentiment score
8.0
AWS Fargate's serverless features boost ROI, scalability, and cost-efficiency, enhancing business operations and customer experience.
The pay-as-you-go pricing model of AWS Fargate was one of the major drivers for us to move there because we reduced costs while increasing the quality of the processing services by about 30%.
 

Customer Service

Sentiment score
6.1
Apache Spark support ranges from vibrant community help to paid vendor plans, with experiences varying based on user needs.
Sentiment score
7.1
AWS Fargate users appreciate support, proactive engagement, and smooth operation, with room for improvement in communication.
Even though we didn't contract support, every two weeks I had a 30-minute meeting with a cloud architect from AWS to help our team use different products of AWS, especially with SageMaker for a forecasting algorithm we were developing.
 

Scalability Issues

Sentiment score
7.7
Apache Spark is scalable, efficiently manages large workloads, and is praised for stability, adaptability, and expansive capabilities.
Sentiment score
8.4
AWS Fargate offers efficient auto-scaling, high performance, and flexibility, effectively managing large-scale operations and fluctuating demands.
 

Stability Issues

Sentiment score
7.5
Apache Spark is stable and reliable, with improved versions addressing issues, widely used by major tech companies.
Sentiment score
8.2
AWS Fargate is stable and reliable for moderate traffic, rated nine out of ten with proper configuration and Lambda function use.
 

Room For Improvement

AWS Fargate is costly, hard to configure, requiring expertise, with users desiring better documentation, scaling, monitoring, and error handling.
For a company that does not require complexity or managing Kubernetes clusters, AWS Fargate is a great way to go.
 

Setup Cost

AWS Fargate is valued for enterprise flexibility despite higher costs, with discounts easing expenses compared to ECS and Lambda.
 

Valuable Features

AWS Fargate simplifies deployment with serverless architecture, minimizing management and costs, while enhancing efficiency and supporting scalable cloud-native microservices.
One of the best features of AWS Fargate is that it was useful for us because we didn't require to run container workloads and we didn't need to deal with the management of a Kubernetes cluster directly, and the ability to run those workloads just in a scheduled manner is also a great feature.
 

Categories and Ranking

Apache Spark
Ranking in Compute Service
4th
Average Rating
8.4
Reviews Sentiment
7.4
Number of Reviews
66
Ranking in other categories
Hadoop (1st), Java Frameworks (2nd)
AWS Fargate
Ranking in Compute Service
2nd
Average Rating
8.6
Reviews Sentiment
7.3
Number of Reviews
18
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of June 2025, in the Compute Service category, the mindshare of Apache Spark is 11.4%, up from 10.8% compared to the previous year. The mindshare of AWS Fargate is 14.0%, down from 18.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Compute Service
 

Featured Reviews

Dunstan Matekenya - PeerSpot reviewer
Open-source solution for data processing with portability
Apache Spark is known for its ease of use. Compared to other available data processing frameworks, it is user-friendly. While many choices now exist, Spark remains easy to use, particularly with Python. You can utilize familiar programming styles similar to Pandas in Python, including object-oriented programming. Another advantage is its portability. I can prototype and perform some initial tasks on my laptop using Spark without needing to be on Databricks or any cloud platform. I can transfer it to Databricks or other platforms, such as AWS. This flexibility allows me to improve processing even on my laptop. For instance, if I'm processing large amounts of data and find my laptop becoming slow, I can quickly switch to Spark. It handles small and large datasets efficiently, making it a versatile tool for various data processing needs.
Subrata Mukherjee - PeerSpot reviewer
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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Top Industries

By visitors reading reviews
Financial Services Firm
27%
Computer Software Company
13%
Manufacturing Company
7%
Comms Service Provider
6%
Financial Services Firm
23%
Computer Software Company
14%
Government
8%
Comms Service Provider
8%
 

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.
What is your experience regarding pricing and costs for Apache Spark?
Apache Spark is open-source, so it doesn't incur any charges.
What needs improvement with Apache Spark?
There is complexity when it comes to understanding the whole ecosystem, especially for beginners. I find it quite complex to understand how a Spark job is initiated, the roles of driver nodes, work...
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...
What needs improvement with AWS Fargate?
The monitoring capabilities of AWS Fargate could be improved and made more robust. The error handling aspect sometimes causes issues and can get stuck during deployment, making the process not very...
What advice do you have for others considering AWS Fargate?
I would recommend AWS Fargate as an alternative to AWS Lambda for running loads or hosting a service. It is a good service for keeping instances running, which minimizes initial latency. Overall, I...
 

Comparisons

 

Overview

 

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
Find out what your peers are saying about AWS Fargate vs. Apache Spark and other solutions. Updated: June 2025.
856,873 professionals have used our research since 2012.