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."It is useful for handling large amounts of data. It is very useful for scientific purposes."
"Provides a lot of good documentation compared to other solutions."
"Spark can handle small to huge data and is suitable for any size of company."
"The deployment of the product is easy."
"One of the key features is that Apache Spark is a distributed computing framework. You can help multiple slaves and distribute the workload between them."
"Features include machine learning, real time streaming, and data processing."
"The solution has been very stable."
"Its scalability and speed are very valuable. You can scale it a lot. It is a great technology for big data. It is definitely better than a lot of earlier warehouse or pipeline solutions, such as Informatica. Spark SQL is very compliant with normal SQL that we have been using over the years. This makes it easy to code in Spark. It is just like using normal SQL. You can use the APIs of Spark or you can directly write SQL code and run it. This is something that I feel is useful in Spark."
"The solution helps us to manage and scale automatically whenever there is a limit to the increase in the application workflow."
"Needs to provide an internal schedule to schedule spark jobs with monitoring capability."
"Stability in terms of API (things were difficult, when transitioning from RDD to DataFrames, then to DataSet)."
"Dynamic DataFrame options are not yet available."
"The solution needs to optimize shuffling between workers."
"Apache Spark provides very good performance The tuning phase is still tricky."
"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 setup I worked on was really complex."
"We are building our own queries on Spark, and it can be improved in terms of query handling."
"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.
