Amazon EC2 vs Apache Spark comparison

Amazon Web Services (AWS) and Apache are both solutions in the Compute Service category. Amazon Web Services (AWS) is ranked #6 with an average rating of 8.6, while Apache is ranked #5 with an average rating of 8.6. Amazon Web Services (AWS) holds a 5.4% mindshare in CS, compared to Apache’s 11.3% mindshare. Additionally, 98% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 90% of Apache users who would recommend it.

Amazon EC2

Read 67 Amazon EC2 reviews

1,034 Views
674 Comparison Views

98% willing to recommend

Apache Spark

Read 66 Apache Spark reviews

1,415 Views
1,077 Comparison Views

90% willing to recommend

Amazon EC2

Apache Spark

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Executive Summary

We performed a comparison between Amazon EC2 and Apache Spark 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 Amazon EC2 vs. Apache Spark Report (Updated: April 2025).

Buyer's Guide

Amazon EC2 vs. Apache Spark

April 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

Amazon EC2

Ranking in Compute Service

6th

Average Rating

8.6

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Apache Spark

Ranking in Compute Service

5th

Average Rating

8.4

Reviews Sentiment

7.7

Number of Reviews

Ranking in other categories

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

Mindshare comparison

As of May 2025, in the Compute Service category, the mindshare of Amazon EC2 is 5.4%, down from 7.6% compared to the previous year. The mindshare of Apache Spark is 11.3%, up from 10.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Compute Service

Featured Reviews

KatlegoMabila

Senior AWS Account Manager at Silicon Overdrive

Offers customization and flexibility with great support

Scalability depends on whether the client wants to scale up or scale down. It decreases resources based on demand. The great aspect of scalability is the flexibility to allow business success to optimize resource solutions and cost efficiency. Another crucial aspect of scalability is auto-scaling. When you have the opportunity to auto-scale, it can't always be available for everything. If you have chosen to integrate with auto-scaling, it's marvellous and doesn't require additional effort. Auto-scaling gives you the edge by using the capacity you have efficiently, scaling up or down as needed. These flexibilities within the EC2 feature instances of AWS play a crucial role in helping me utilize AWS EC2 Intelligent efficiently.

Read full review

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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Quotes from Members

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

Pros

"What we have found most valuable is that we have not lost stability in the program."

"One of the most valuable features of EC2 is its accessibility; I can easily access it through various tools like GIT and use it on mobile devices."

"What I found most valuable in Amazon EC2 is that you only pay for what you use, versus an on-premise deployment that requires you to pay for the cost of the server. When it's on-premise, you'll need to meet more specifications and requirements, and the purchasing process even takes time. As Amazon EC2 is cloud-based, you'll only pay when you use the service."

"The most valuable feature of this solution is the ability to have standard operating systems along with the Windows, Linux operating systems, and their maintenance-free structure, which we prefer."

"The ethernet configuration is stable and the product is reliable."

"The flexibility of the security features is what is interesting."

"The product is easy to set up."

"Stable, scalable, and simple to implement."

More Amazon EC2 pros

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

"The data processing framework is good."

"It is highly scalable, allowing you to efficiently work with extensive datasets that might be problematic to handle using traditional tools that are memory-constrained."

"It is useful for handling large amounts of data. It is very useful for scientific purposes."

"Now, when we're tackling sentiment analysis using NLP technologies, we deal with unstructured data—customer chats, feedback on promotions or demos, and even media like images, audio, and video files. For processing such data, we rely on PySpark. Beneath the surface, Spark functions as a compute engine with in-memory processing capabilities, enhancing performance through features like broadcasting and caching. It's become a crucial tool, widely adopted by 90% of companies for a decade or more."

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

"AI libraries are the most valuable. They provide extensibility and usability. Spark has a lot of connectors, which is a very important and useful feature for AI. You need to connect a lot of points for AI, and you have to get data from those systems. Connectors are very wide in Spark. With a Spark cluster, you can get fast results, especially for AI."

"I appreciate everything about the solution, not just one or two specific features. The solution is highly stable. I rate it a perfect ten. The solution is highly scalable. I rate it a perfect ten. The initial setup was straightforward. I recommend using the solution. Overall, I rate the solution a perfect ten."

More Apache Spark pros

Cons

"EC2 is a little expensive."

"They have to provide clarity on pricing. It's not transparent."

"The price could be better, and it could be more affordable. Because I run my own servers, the prices are quite high."

"It is a little too expensive."

"Currently in the autoscaling process if we have multiple issues we are not able to connect some of the VPC through the SMS."

"Amazon EC2 could improve the stability."

"The IP changes whenever we restart which is frustrating."

"The availability and response time of the free technical support can be improved."

More Amazon EC2 cons

"I would like to see integration with data science platforms to optimize the processing capability for these tasks."

"It needs a new interface and a better way to get some data. In terms of writing our scripts, some processes could be faster."

"We are building our own queries on Spark, and it can be improved in terms of query handling."

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

"This solution currently cannot support or distribute neural network related models, or deep learning related algorithms. We would like this functionality to be developed."

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

"It should support more programming languages."

"It's not easy to install."

More Apache Spark cons

Pricing and Cost Advice

"The clients have found the billing of Amazon EC2 good, but the price could be less high. There is a monthly subscription to use the solution."

"The use of Amazon EC2 does not incur any licensing fees."

"You pay as you use it."

"I use the free tier, although I have paid for some services that are not free. The overall cost of this solution depends on the services you use."

"The licensing of Amazon EC2 is expensive. Microsoft Windows Servers are expensive to license."

"The price of Amazon EC2 could improve. The Google Cloud Platform is more cost-effective."

"Reducing the price of the solution could lead to an improvement."

"We are paying about $1,500 a month for one of the services."

More Amazon EC2 pricing and cost advice

"Apache Spark is an open-source tool."

"The tool is an open-source product. If you're using the open-source Apache Spark, no fees are involved at any time. Charges only come into play when using it with other services like Databricks."

"I did not pay anything when using the tool on cloud services, but I had to pay on the compute side. The tool is not expensive compared with the benefits it offers. I rate the price as an eight out of ten."

"It is quite expensive. In fact, it accounts for almost 50% of the cost of our entire project."

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

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

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

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

More Apache Spark pricing and cost advice

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Top Industries

By visitors reading reviews

Computer Software Company

19%

Financial Services Firm

16%

Manufacturing Company

University

Financial Services Firm

26%

Computer Software Company

13%

Manufacturing Company

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about Amazon EC2?

The scalability and elasticity are helpful.

See all answers

What is your experience regarding pricing and costs for Amazon EC2?

I'm going to mention again that there is quite a bit of complexity within the pricing of EC2 instances. I'm just going to give it six out of ten since there are various standards, upfront and commi...

See all answers

What needs improvement with Amazon EC2?

There is not much to be improved or enhanced. One of the things that need to be looked into is the complex pricing, which is rather intense. Sometimes, clients don't understand the structures. Thes...

See all answers

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?

Apache Spark is open-source, so it doesn't incur any charges.

See all answers

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...

See all answers

Comparisons

AWS Fargate vs Amazon EC2

Compared 27% of the time

AWS Batch vs Amazon EC2

Compared 25% of the time

AWS Lambda vs Amazon EC2

Compared 17% of the time

Google Compute Engine vs Amazon EC2

Compared 12% of the time

More Amazon EC2 Competitors

Spring Boot vs Apache Spark

Compared 27% of the time

AWS Batch vs Apache Spark

Compared 12% of the time

SAP HANA vs Apache Spark

Compared 11% of the time

Spark SQL vs Apache Spark

Compared 7% of the time

Cloudera Distribution for Hadoop vs Apache Spark

Compared 7% of the time

More Apache Spark Competitors

Product Reports

Buyer's Guide

Amazon EC2

May 2025

Download Amazon EC2 product report

Buyer's Guide

Apache Spark

May 2025

Download Apache Spark product report

Also Known As

Amazon Elastic Compute Cloud, EC2

No data available

Overview

Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides secure, resizable compute capacity in the cloud. It is designed to make web-scale cloud computing easier for developers.

Amazon EC2’s simple web service interface allows you to obtain and configure capacity with minimal friction. It provides you with complete control of your computing resources and lets you run on Amazon’s proven computing environment. Amazon EC2 reduces the time required to obtain and boot new server instances to minutes, allowing you to quickly scale capacity, both up and down, as your computing requirements change. Amazon EC2 changes the economics of computing by allowing you to pay only for capacity that you actually use. Amazon EC2 provides developers the tools to build failure resilient applications and isolate them from common failure scenarios.

Amazon Web Services (AWS)

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

Apache

Sample Customers

Netflix, Expedia, TimeInc., Novaris, airbnb, Lamborghini

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

Buyer's Guide

Amazon EC2 vs. Apache Spark

April 2025

Free Report: Amazon EC2 vs. Apache Spark

Find out what your peers are saying about Amazon EC2 vs. Apache Spark and other solutions. Updated: April 2025.

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