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 #5 with an average rating of 8.6, while Apache is ranked #4 with an average rating of 8.7. Amazon Web Services (AWS) holds a 6.8% 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 63 Amazon EC2 reviews

1,766 Views
1,259 Comparison Views

98% willing to recommend

Apache Spark

Read 64 Apache Spark reviews

2,061 Views
1,606 Comparison Views

90% willing to recommend

Amazon EC2

Apache Spark

Comparison Buyer's Guide

Download the report

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: October 2024).

Buyer's Guide

Amazon EC2 vs. Apache Spark

October 2024

Download the complete report

Helped 816,406 peers since 2012

Categories and Ranking

Amazon EC2

Ranking in Compute Service

5th

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 November 2024, in the Compute Service category, the mindshare of Amazon EC2 is 6.8%, up from 6.6% compared to the previous year. The mindshare of Apache Spark is 11.2%, up from 7.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Compute Service

Featured Reviews

Julius Mboya

Chief technical officer at Solvezy Technology Kenya Limited

Ensures we can provision resources on demand, and we can grow and shrink them as per the traffic

We faced a challenge in regard to billing. There was a time when we were working on changing the mode of payment from card to wire. It took a lot of time because our state is set up in Kenya, so we needed to pay in Kenya currency. We have to go around in circles. There was a lot of documentation required, but we managed to go through successfully.

Read full review

SurjitChoudhury

Data engineer at Cocos pt

Offers batch processing of data and in-memory processing in Spark greatly enhances performance

Spark supports real-time data processing through Spark Streaming. It allows for batch processing of data. If you have immediate data, like chat information, that needs to be processed in real-time, Spark Streaming is used. For data that can be evaluated later, batch processing with Apache Spark is suitable. Mostly, batch processing is utilized in our organization, but for streaming data processing, tools like Kafka are often integrated. In-memory processing in Spark greatly enhances performance, making it a hundred times faster than the previous MapReduce methods. This improvement is achieved through optimization techniques like caching, broadcasting, and partitioning, which help in optimizing queries for faster processing.

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

"Stable, scalable, and simple to implement."

"My favorite feature of this solution is the flexibility of instance types, which allows for the cost to be tailored to the usage amount and type."

"The platform has been quite stable and reliable."

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

"The amount of bandwidth has been most valuable."

"The ability to bring up servers and then do the computation and deposit means we don't have to maintain a data center. Everything is virtual and the security is also taken care of. It helps us to achieve compliance. Being a small startup with the security features that AWS provides helps us with compliance."

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

"Amazon EC2 allows us to create different regions and availability zones based upon application needs."

More Amazon EC2 pros

"There's a lot of functionality."

"I feel the streaming is its best feature."

"DataFrame: Spark SQL gives the leverage to create applications more easily and with less coding effort."

"The product's deployment phase is easy."

"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."

"The scalability has been the most valuable aspect of the solution."

"The product’s most valuable features are lazy evaluation and workload distribution."

"Its scalability and speed are very valuable. You can scale it a lot. It is a great technology for big data. It is definitely better than a lot of earlier warehouse or pipeline solutions, such as Informatica. Spark SQL is very compliant with normal SQL that we have been using over the years. This makes it easy to code in Spark. It is just like using normal SQL. You can use the APIs of Spark or you can directly write SQL code and run it. This is something that I feel is useful in Spark."

More Apache Spark pros

Cons

"I think the whole AWS stack is very disconnected from each other. in the .NET space, everything just works nicely together. In the AWS stack, there is a lot of head scratching."

"Amazon EC2 could improve by reducing the price."

"I would like to see as much automation for data validation as possible in the future."

"Pricing-wise, it is a bit high."

"Amazon EC2 could improve by having integration with other cloud systems, such as Azure, and Google Cloud which would be good. Additionally, having integration with on-premise systems would be appreciated."

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

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

"Nothing is really missing in terms of features."

More Amazon EC2 cons

"More ML based algorithms should be added to it, to make it algorithmic-rich for developers."

"Apart from the restrictions that come with its in-memory implementation. It has been improved significantly up to version 3.0, which is currently in use."

"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."

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

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

"Stream processing needs to be developed more in Spark. I have used Flink previously. Flink is better than Spark at stream processing."

"Dynamic DataFrame options are not yet available."

"Apache Spark lacks geospatial data."

More Apache Spark cons

Pricing and Cost Advice

"It's expensive, and it could be cheaper."

"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."

"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."

"It is not an expensive solution."

"It's competitive but can vary based on instance types and usage patterns."

"The solution has different pricing models, and its cost differs when you purchase it for one year or three years."

"The price is reasonable, but there is definitely an opportunity to lower it in instances which are of a higher configuration, because they have been typically used for the long term."

More Amazon EC2 pricing and cost advice

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

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

"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."

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

"Since we are using the Apache Spark version, not the data bricks version, it is an Apache license version, the support and resolution of the bug are actually late or delayed. The Apache license is free."

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

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

"Licensing costs can vary. For instance, when purchasing a virtual machine, you're asked if you want to take advantage of the hybrid benefit or if you prefer the license costs to be included upfront by the cloud service provider, such as Azure. If you choose the hybrid benefit, it indicates you already possess a license for the operating system and wish to avoid additional charges for that specific VM in Azure. This approach allows for a reduction in licensing costs, charging only for the service and associated resources."

More Apache Spark pricing and cost advice

See which vendors are best for you

Use our free recommendation engine to learn which Compute Service solutions are best for your needs.

See recommendations

816,406 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

23%

Computer Software Company

18%

Retailer

Manufacturing Company

Financial Services Firm

27%

Computer Software Company

13%

Manufacturing Company

University

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?

We are paying about $1,500 a month for one of the services. I'd rate the pricing as six out of ten for being expensive.

See all answers

What needs improvement with Amazon EC2?

The pricing model could be improved. We found Amazon EC2 to be pricey.

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 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...

See all answers

Comparisons

AWS Fargate vs Amazon EC2

Compared 49% of the time

AWS Batch vs Amazon EC2

Compared 15% of the time

AWS Lambda vs Amazon EC2

Compared 7% of the time

Apache NiFi vs Amazon EC2

Compared 6% of the time

Google App Engine vs Amazon EC2

Compared 5% of the time

More Amazon EC2 Competitors

Spring Boot vs Apache Spark

Compared 30% of the time

SAP HANA vs Apache Spark

Compared 11% of the time

AWS Batch vs Apache Spark

Compared 11% of the time

Cloudera Distribution for Hadoop vs Apache Spark

Compared 8% of the time

Amazon EMR vs Apache Spark

Compared 2% of the time

More Apache Spark Competitors

Product Reports

Buyer's Guide

Amazon EC2

November 2024

Download Amazon EC2 product report

Buyer's Guide

Apache Spark

November 2024

Download Apache Spark product report

Also Known As

Amazon Elastic Compute Cloud, EC2

No data available

Learn More

Amazon Web Services (AWS)

Apache

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.

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

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

October 2024

Free Report: Amazon EC2 vs. Apache Spark

Find out what your peers are saying about Amazon EC2 vs. Apache Spark and other solutions. Updated: October 2024.

DOWNLOAD NOW

816,406 professionals have used our research since 2012.

See our Amazon EC2 vs. Apache Spark report.

See our list of best Compute Service vendors.

We monitor all Compute Service reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.