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's easy to prepare parallelism in Spark, run the solution with specific parameters, and get good performance."
"The solution has been very stable."
"Apache Spark provides a very high-quality implementation of distributed data processing."
"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."
"Provides a lot of good documentation compared to other solutions."
"Apache Spark can do large volume interactive data analysis."
"The fault tolerant feature is provided."
"Now, when we're tackling sentiment analysis using NLP technologies, we deal with unstructured data—customer chats, feedback on promotions or demos, and even media like images, audio, and video files. For processing such data, we rely on PySpark. Beneath the surface, Spark functions as a compute engine with in-memory processing capabilities, enhancing performance through features like broadcasting and caching. It's become a crucial tool, widely adopted by 90% of companies for a decade or more."
"The solution helps us to manage and scale automatically whenever there is a limit to the increase in the application workflow."
"The migration of data between different versions could be improved."
"At the initial stage, the product provides no container logs to check the activity."
"Apache Spark could potentially improve in terms of user-friendliness, particularly for individuals with a SQL background. While it's suitable for those with programming knowledge, making it more accessible to those without extensive programming skills could be beneficial."
"The initial setup was not easy."
"When you are working with large, complex tasks, the garbage collection process is slow and affects performance."
"The solution’s integration with other platforms should be improved."
"Apache Spark provides very good performance The tuning phase is still tricky."
"It would be beneficial to enhance Spark's capabilities by incorporating models that utilize features not traditionally present in its framework."
"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.