We performed a comparison between Apache Spark and Eclipse MicroProfile based on real PeerSpot user reviews.
Find out in this report how the two Java Frameworks solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The scalability has been the most valuable aspect of the solution."
"It's easy to prepare parallelism in Spark, run the solution with specific parameters, and get good performance."
"I found the solution stable. We haven't had any problems with it."
"The good performance. The nice graphical management console. The long list of ML algorithms."
"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."
"The product's deployment phase is easy."
"The main feature that we find valuable is that it is very fast."
"The distribution of tasks, like the seamless map-reduce functionality, is quite impressive."
"We use the solution to create microservices."
"Provides a lightweight runtime."
"The solution is stable."
"It needs a new interface and a better way to get some data. In terms of writing our scripts, some processes could be faster."
"When you are working with large, complex tasks, the garbage collection process is slow and affects performance."
"Spark could be improved by adding support for other open-source storage layers than Delta Lake."
"The solution needs to optimize shuffling between workers."
"If you have a Spark session in the background, sometimes it's very hard to kill these sessions because of D allocation."
"When you first start using this solution, it is common to run into memory errors when you are dealing with large amounts of data."
"Apache Spark provides very good performance The tuning phase is still tricky."
"Apache Spark's GUI and scalability could be improved."
"Deployment of microservers in the Kubernetes environment is difficult."
"The tool needs to improve its messaging."
"Its performance speed could be improved while working on the browser."
Apache Spark is ranked 2nd in Java Frameworks with 60 reviews while Eclipse MicroProfile is ranked 6th in Java Frameworks with 3 reviews. Apache Spark is rated 8.4, while Eclipse MicroProfile is rated 8.4. The top reviewer of Apache Spark writes "Reliable, able to expand, and handle large amounts of data well". On the other hand, the top reviewer of Eclipse MicroProfile writes "Scalable solution with an easy initial setup process". Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and Cloudera Distribution for Hadoop, whereas Eclipse MicroProfile is most compared with Spring Boot, Jakarta EE, Amazon Corretto, Vert.x and Open Liberty. See our Apache Spark vs. Eclipse MicroProfile report.
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We monitor all Java Frameworks 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.
