We performed a comparison between Apache Spark Streaming and SAS Event Stream Processing based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Confluent and others in Streaming Analytics."It's the fastest solution on the market with low latency data on data transformations."
"As an open-source solution, using it is basically free."
"Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows."
"Apache Spark Streaming's most valuable feature is near real-time analytics. The developers can build APIs easily for a code-steaming pipeline. The solutions have an ecosystem of integration with other stock services."
"The solution is better than average and some of the valuable features include efficiency and stability."
"The solution is very stable and reliable."
"Apache Spark Streaming was straightforward in terms of maintenance. It was actively developed, and migrating from an older to a newer version was quite simple."
"Apache Spark Streaming has features like checkpointing and Streaming API that are useful."
"The solution is beneficial on an enterprise level."
"It was resource-intensive, even for small-scale applications."
"There could be an improvement in the area of the user configuration section, it should be less developer-focused and more business user-focused."
"The cost and load-related optimizations are areas where the tool lacks and needs improvement."
"We would like to have the ability to do arbitrary stateful functions in Python."
"In terms of improvement, the UI could be better."
"The solution itself could be easier to use."
"The service structure of Apache Spark Streaming can improve. There are a lot of issues with memory management and latency. There is no real-time analytics. We recommend it for the use cases where there is a five-second latency, but not for a millisecond, an IOT-based, or the detection anomaly-based. Flink as a service is much better."
"The initial setup is quite complex."
"The persistence could be better."
Apache Spark Streaming is ranked 8th in Streaming Analytics with 8 reviews while SAS Event Stream Processing is ranked 14th in Streaming Analytics with 1 review. Apache Spark Streaming is rated 8.0, while SAS Event Stream Processing is rated 8.0. The top reviewer of Apache Spark Streaming writes "Easy integration, beneficial auto-scaling, and good open-sourced support community". On the other hand, the top reviewer of SAS Event Stream Processing writes "A solution with useful windowing features and great for operations and marketing". Apache Spark Streaming is most compared with Amazon Kinesis, Azure Stream Analytics, Spring Cloud Data Flow, Confluent and Databricks, whereas SAS Event Stream Processing is most compared with Apache Flink.
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We monitor all Streaming Analytics 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.
