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 8.8, while Apache is ranked #4 with an average rating of 8.6. Amazon Web Services (AWS) holds a 5.7% mindshare in CS, compared to Apache’s 11.2% 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 65 Amazon EC2 reviews

1,179 Views
773 Comparison Views

98% willing to recommend

Apache Spark

Read 65 Apache Spark reviews

1,526 Views
1,149 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: March 2025).

Buyer's Guide

Amazon EC2 vs. Apache Spark

March 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

4th

Average Rating

8.4

Reviews Sentiment

7.7

Number of Reviews

Ranking in other categories

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

Mindshare comparison

As of April 2025, in the Compute Service category, the mindshare of Amazon EC2 is 5.7%, down from 7.5% compared to the previous year. The mindshare of Apache Spark is 11.2%, up from 9.7% 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.

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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.

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

"The product is easy to set up."

"I believe that cloud solutions are better than physical servers."

"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."

"The most valuable features of Amazon EC2 are content delivery and adaptability."

"The most valuable features of Amazon EC2 are ease of use and the services offered."

"The Key Management Service (KMS) feature is very helpful for security. It encrypts the data that is being saved. Cloud storage is also very helpful, and it could be AWS S3, which a lot of people use."

"We don't have to worry about scalability issues or maintenance or security. It's all taken care of."

"Amazon EC2's flexibility and ease of configuration were found to be very valuable."

More Amazon EC2 pros

"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."

"One of Apache Spark's most valuable features is that it supports in-memory processing, the execution of jobs compared to traditional tools is very fast."

"Apache Spark provides a very high-quality implementation of distributed data processing."

"The most valuable feature of Apache Spark is its ease of use."

"With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware."

"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."

"Apache Spark is known for its ease of use. Compared to other available data processing frameworks, it is user-friendly."

"I like that it can handle multiple tasks parallelly. I also like the automation feature. JavaScript also helps with the parallel streaming of the library."

More Apache Spark pros

Cons

"Amazon EC2's pricing could be better."

"Amazon EC2 is very expensive, and it would be helpful if they decreased the pricing."

"An area needing improvement is the time limitations when accessing EC2 instances."

"In terms of improvement, they could build some client-side desktop tools that provide easier connectivity to Amazon."

"Regional acceleration could improve. If I am hosting a website and I want the experience to be faster they should have this feature to allow for increased speeds."

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

"We have had some downtime using the solution."

"The monitoring part could be improved. When we're building and configuring things or doing database replication, EC2's monitoring could provide more information. It's hard to find the information I need in the graphs they provide."

More Amazon EC2 cons

"The management tools could use improvement. Some of the debugging tools need some work as well. They need to be more descriptive."

"At times during the deployment process, the tool goes down, making it look less robust. To take care of the issues in the deployment process, users need to do manual interventions occasionally."

"It requires overcoming a significant learning curve due to its robust and feature-rich nature."

"The setup I worked on was really complex."

"Stability in terms of API (things were difficult, when transitioning from RDD to DataFrames, then to DataSet)."

"Apache Spark could improve the connectors that it supports. There are a lot of open-source databases in the market. For example, cloud databases, such as Redshift, Snowflake, and Synapse. Apache Spark should have connectors present to connect to these databases. There are a lot of workarounds required to connect to those databases, but it should have inbuilt connectors."

"The Spark solution could improve in scheduling tasks and managing dependencies."

"Technical expertise from an engineer is required to deploy and run high-tech tools, like Informatica, on Apache Spark, making it an area where improvements are required to make the process easier for users."

More Apache Spark cons

Pricing and Cost Advice

"The price can be improved."

"For our usage, the cost is approximately $20,000 to $23,000 per month."

"We are using a pay-as-you-go model."

"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."

"There is a license required to use this solution and we pay on a monthly basis."

"I am using the tier three Amazon service. I am not going to use another solution other than Amazon EC2 because here in Pakistan there are some payment issues for solutions abroad."

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

More Amazon EC2 pricing and cost advice

"Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera."

"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."

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

"Apache Spark is not too cheap. You have to pay for hardware and Cloudera licenses. Of course, there is a solution with open source without Cloudera."

"On the cloud model can be expensive as it requires substantial resources for implementation, covering on-premises hardware, memory, and licensing."

"Apache Spark is an open-source tool."

"They provide an open-source license for the on-premise version."

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

More Apache Spark pricing and cost advice

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Top Industries

By visitors reading reviews

Computer Software Company

20%

Financial Services Firm

14%

Manufacturing Company

Retailer

Financial Services Firm

28%

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?

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 Spark solution could improve in scheduling tasks and managing dependencies. Spark alone cannot handle sequential tasks, requiring environments like Airflow scheduler or scripts. For instance, o...

See all answers

Comparisons

AWS Fargate vs Amazon EC2

Compared 40% of the time

AWS Batch vs Amazon EC2

Compared 27% of the time

AWS Lambda vs Amazon EC2

Compared 20% of the time

More Amazon EC2 Competitors

Spring Boot vs Apache Spark

Compared 27% of the time

SAP HANA vs Apache Spark

Compared 12% of the time

AWS Batch vs Apache Spark

Compared 12% of the time

Cloudera Distribution for Hadoop vs Apache Spark

Compared 8% of the time

Spark SQL vs Apache Spark

Compared 7% of the time

More Apache Spark Competitors

Product Reports

Buyer's Guide

Amazon EC2

March 2025

Download Amazon EC2 product report

Buyer's Guide

Apache Spark

March 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

March 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: March 2025.

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