We performed a comparison between Apache Flink and SAS Event Stream Processing based on real PeerSpot user reviews.
Find out what your peers are saying about Amazon Web Services (AWS), Databricks, Microsoft and others in Streaming Analytics."It provides us the flexibility to deploy it on any cluster without being constrained by cloud-based limitations."
"The product helps us to create both simple and complex data processing tasks. Over time, it has facilitated integration and navigation across multiple data sources tailored to each client's needs. We use Apache Flink to control our clients' installations."
"Easy to deploy and manage."
"The setup was not too difficult."
"Apache Flink allows you to reduce latency and process data in real-time, making it ideal for such scenarios."
"The event processing function is the most useful or the most used function. The filter function and the mapping function are also very useful because we have a lot of data to transform. For example, we store a lot of information about a person, and when we want to retrieve this person's details, we need all the details. In the map function, we can actually map all persons based on their age group. That's why the mapping function is very useful. We can really get a lot of events, and then we keep on doing what we need to do."
"Apache Flink's best feature is its data streaming tool."
"The top feature of Apache Flink is its low latency for fast, real-time data. Another great feature is the real-time indicators and alerts which make a big difference when it comes to data processing and analysis."
"The solution is beneficial on an enterprise level."
"The state maintains checkpoints and they use RocksDB or S3. They are good but sometimes the performance is affected when you use RocksDB for checkpointing."
"There is room for improvement in the initial setup process."
"Apache Flink should improve its data capability and data migration."
"The machine learning library is not very flexible."
"PyFlink is not as fully featured as Python itself, so there are some limitations to what you can do with it."
"We have a machine learning team that works with Python, but Apache Flink does not have full support for the language."
"In a future release, they could improve on making the error descriptions more clear."
"Amazon's CloudFormation templates don't allow for direct deployment in the private subnet."
"The persistence could be better."
Apache Flink is ranked 5th in Streaming Analytics with 15 reviews while SAS Event Stream Processing is ranked 14th in Streaming Analytics with 1 review. Apache Flink is rated 7.6, while SAS Event Stream Processing is rated 8.0. The top reviewer of Apache Flink writes "A great solution with an intricate system and allows for batch data processing". 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 Flink is most compared with Amazon Kinesis, Spring Cloud Data Flow, Databricks, Azure Stream Analytics and PubSub+ Event Broker, whereas SAS Event Stream Processing is most compared with Apache Spark Streaming.
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