We performed a comparison between Apache Flink and Software AG Apama 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."Apache Flink is meant for low latency applications. You take one event opposite if you want to maintain a certain state. When another event comes and you want to associate those events together, in-memory state management was a key feature for us."
"It is user-friendly and the reporting is good."
"With Flink, it provides out-of-the-box checkpointing and state management. It helps us in that way. When Storm used to restart, sometimes we would lose messages. With Flink, it provides guaranteed message processing, which helped us. It also helped us with maintenance or restarts."
"Easy to deploy and manage."
"This is truly a real-time solution."
"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."
"The documentation is very good."
"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 most valuable feature of the solution is the ability that it provides its users to handle different kinds of rules."
"The machine learning library is not very flexible."
"We have a machine learning team that works with Python, but Apache Flink does not have full support for the language."
"There is room for improvement in the initial setup process."
"The solution could be more user-friendly."
"In terms of improvement, there should be better reporting. You can integrate with reporting solutions but Flink doesn't offer it themselves."
"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."
"In terms of stability with Flink, it is something that you have to deal with every time. Stability is the number one problem that we have seen with Flink, and it really depends on the kind of problem that you're trying to solve."
"Apache Flink's documentation should be available in more languages."
"The ease of development and maintenance should be enhanced, but it is difficult due to the use of the proprietary programming language in the product."
Apache Flink is ranked 5th in Streaming Analytics with 15 reviews while Software AG Apama is ranked 17th in Streaming Analytics with 1 review. Apache Flink is rated 7.6, while Software AG Apama is rated 7.0. 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 Software AG Apama writes "A tool to send out promotional notifications that need to improve areas, like deployment and maintenance". Apache Flink is most compared with Amazon Kinesis, Spring Cloud Data Flow, Databricks, Azure Stream Analytics and Apache Pulsar, whereas Software AG Apama is most compared with Oracle BAM and TIBCO Streambase CEP.
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