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."The most important aspects are that the solution is scalable and easy to manage."
"The product is very mature and organized."
"All of my lower maintenance overheads are taken care of. I don't have to worry about it."
"The most valuable features of Amazon EC2 are ease of use and the services offered."
"EC2 has the typical advantages of using the cloud. It's easy to provision and set up."
"The most valuable feature is autoscaling."
"We don't have to worry about scalability issues or maintenance or security. It's all taken care of."
"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."
"It's easy to prepare parallelism in Spark, run the solution with specific parameters, and get good performance."
"There's a lot of functionality."
"The features we find most valuable are the machine learning, data learning, and Spark Analytics."
"The product’s most valuable feature is the SQL tool. It enables us to create a database and publish it."
"I feel the streaming is its best feature."
"The solution has been very stable."
"Provides a lot of good documentation compared to other solutions."
"The good performance. The nice graphical management console. The long list of ML algorithms."
"The IP changes whenever we restart which is frustrating."
"The initial setup could be easier because many keys are required for access."
"We're expecting to have Graviton instances. Graviton means it's not internal, it's a low-cost instance. At present time, Graviton is not supported for a few packages."
"If the solution was cheaper, if the price was less, it would be better."
"Technical itself could be a bit more helpful, especially when it comes to integration assistance. When we talk to the technical team, often it's some issue with integration and they'll tell us to talk to the other company. Often, the other company will look at everything and not see an issue from their end and then we are at an impasse."
"We have had some downtime using the solution."
"I would like to see improvement in the information available up-front for users around tailoring the package to their actual requirements. At present it can take time to work with the on demand instance until you are used to what features are right for the user."
"The scalability could improve."
"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."
"Apache Spark's GUI and scalability could be improved."
"It should support more programming languages."
"I know there is always discussion about which language to write applications in and some people do love Scala. However, I don't like it."
"This solution currently cannot support or distribute neural network related models, or deep learning related algorithms. We would like this functionality to be developed."
"One limitation is that not all machine learning libraries and models support it."
"At the initial stage, the product provides no container logs to check the activity."
"Apache Spark is very difficult to use. It would require a data engineer. It is not available for every engineer today because they need to understand the different concepts of Spark, which is very, very difficult and it is not easy to learn."
Amazon EC2 is ranked 4th in Compute Service with 56 reviews while Apache Spark is ranked 5th in Compute Service with 60 reviews. Amazon EC2 is rated 8.6, while Apache Spark is rated 8.4. The top reviewer of Amazon EC2 writes "Highly stable, is auto-scaling, and can be utilized in under five minutes". On the other hand, the top reviewer of Apache Spark writes "Reliable, able to expand, and handle large amounts of data well". Amazon EC2 is most compared with AWS Fargate, AWS Lambda, Apache NiFi, AWS Batch and Google App Engine, whereas Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and Jakarta EE. See our Amazon EC2 vs. Apache Spark report.
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