We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"This is an open-source platform that can be used free of charge."
"Apache Flink is open source so we pay no licensing for the use of the software."
"The solution is open-source, which is free."
"It's an open-source solution."
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Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams. Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale.
WSO2 Stream Processor is an open source, cloud native and lightweight stream processing platform that understands streaming SQL queries in order to capture, analyze, process and act on events in real time. This facilitates real-time streaming analytics and streaming data integration. With the product’s powerful streaming SQL, simple deployment, and ability to adapt to changes rapidly, enterprises can go to market faster and achieve greater ROI. Unlike other offerings, it provides a simple two-node deployment for high availability and scales beyond with its distributed deployment to cater to extremely high workloads.
Apache Flink is ranked 5th in Streaming Analytics with 9 reviews while WSO2 Stream Processor is ranked 18th in Streaming Analytics. Apache Flink is rated 7.6, while WSO2 Stream Processor is rated 0.0. The top reviewer of Apache Flink writes "Scalable framework for stateful streaming aggregations". On the other hand, Apache Flink is most compared with Amazon Kinesis, Spring Cloud Data Flow, Azure Stream Analytics, Google Cloud Dataflow and Informatica Data Engineering Streaming, whereas WSO2 Stream Processor is most compared with Cloudera DataFlow.
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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.