We performed a comparison between Apache Spark and Spot Ocean based on real PeerSpot user reviews.
Find out what your peers are saying about Amazon Web Services (AWS), Apache, Zadara and others in Compute Service."Apache Spark can do large volume interactive data analysis."
"There's a lot of functionality."
"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."
"It is highly scalable, allowing you to efficiently work with extensive datasets that might be problematic to handle using traditional tools that are memory-constrained."
"The distribution of tasks, like the seamless map-reduce functionality, is quite impressive."
"It provides a scalable machine learning library."
"DataFrame: Spark SQL gives the leverage to create applications more easily and with less coding effort."
"I feel the streaming is its best feature."
"The solution helps us to manage and scale automatically whenever there is a limit to the increase in the application workflow."
"If you have a Spark session in the background, sometimes it's very hard to kill these sessions because of D allocation."
"At the initial stage, the product provides no container logs to check the activity."
"Include more machine learning algorithms and the ability to handle streaming of data versus micro batch processing."
"Its UI can be better. Maintaining the history server is a little cumbersome, and it should be improved. I had issues while looking at the historical tags, which sometimes created problems. You have to separately create a history server and run it. Such things can be made easier. Instead of separately installing the history server, it can be made a part of the whole setup so that whenever you set it up, it becomes available."
"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."
"Needs to provide an internal schedule to schedule spark jobs with monitoring capability."
"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."
"They could improve the issues related to programming language for the platform."
"The solution doesn't have support from OCI, and it should start working to onboard OCI."
Apache Spark is ranked 5th in Compute Service with 60 reviews while Spot Ocean is ranked 11th in Compute Service with 1 review. Apache Spark is rated 8.4, while Spot Ocean is rated 7.0. 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 Spot Ocean writes "Used to manage Kubernetes infrastructure, but it doesn't have support from OCI". Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and Cloudera Distribution for Hadoop, whereas Spot Ocean is most compared with Spot Elastigroup and Spot Eco.
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.