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."Its ease of use is 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."
"I use it for NextCloud and for developer purposes."
"This is a user-friendly solution."
"The solution offers good access policies."
"EC2 is secure and stable, and we have no complaints about it on AWS."
"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."
"We find it easy to scale."
"The memory processing engine is the solution's most valuable aspect. It processes everything extremely fast, and it's in the cluster itself. It acts as a memory engine and is very effective in processing data correctly."
"The most valuable feature of this solution is its capacity for processing large amounts of data."
"The main feature that we find valuable is that it is very fast."
"The most valuable feature is the Fault Tolerance and easy binding with other processes like Machine Learning, graph analytics."
"The processing time is very much improved over the data warehouse solution that we were using."
"I feel the streaming is its best feature."
"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."
"The deployment of the product is easy."
"The IP changes whenever we restart which is frustrating."
"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."
"I think the pricing needs to be adjusted and better security."
"Amazon EC2 could improve by reducing the price."
"Amazon EC2 could improve the stability."
"We have had some downtime using the solution."
"Pricing-wise, it is a bit high."
"The product needs to improve its cost management."
"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."
"We've had problems using a Python process to try to access something in a large volume of data. It crashes if somebody gives me the wrong code because it cannot handle a large volume of data."
"There were some problems related to the product's compatibility with a few Python libraries."
"The migration of data between different versions could be improved."
"If you have a Spark session in the background, sometimes it's very hard to kill these sessions because of D allocation."
"Needs to provide an internal schedule to schedule spark jobs with monitoring capability."
"The solution must improve its performance."
"It requires overcoming a significant learning curve due to its robust and feature-rich nature."
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 "Easy to scale and valuable features include the security group and key management". 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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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.
