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."The most valuable feature of Apache Spark is its memory processing because it processes data over RAM rather than disk, which is much more efficient and fast."
"One of Apache Spark's most valuable features is that it supports in-memory processing, the execution of jobs compared to traditional tools is very fast."
"The product is useful for analytics."
"With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware."
"The good performance. The nice graphical management console. The long list of ML algorithms."
"The most valuable feature is the Fault Tolerance and easy binding with other processes like Machine Learning, graph analytics."
"DataFrame: Spark SQL gives the leverage to create applications more easily and with less coding effort."
"The product's deployment phase is easy."
"The solution helps us to manage and scale automatically whenever there is a limit to the increase in the application workflow."
"They could improve the issues related to programming language for the platform."
"When you want to extract data from your HDFS and other sources then it is kind of tricky because you have to connect with those sources."
"At the initial stage, the product provides no container logs to check the activity."
"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."
"Dynamic DataFrame options are not yet available."
"The graphical user interface (UI) could be a bit more clear. It's very hard to figure out the execution logs and understand how long it takes to send everything. If an execution is lost, it's not so easy to understand why or where it went. I have to manually drill down on the data processes which takes a lot of time. Maybe there could be like a metrics monitor, or maybe the whole log analysis could be improved to make it easier to understand and navigate."
"We use big data manager but we cannot use it as conditional data so whenever we're trying to fetch the data, it takes a bit of time."
"The management tools could use improvement. Some of the debugging tools need some work as well. They need to be more descriptive."
"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.
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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.
