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 Amazon Web Services (AWS), Databricks, Microsoft and others in Streaming Analytics."It is user-friendly and the reporting is good."
"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."
"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."
"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."
"Another feature is how Flink handles its radiuses. It has something called the checkpointing concept. You're dealing with billions and billions of requests, so your system is going to fail in large storage systems. Flink handles this by using the concept of checkpointing and savepointing, where they write the aggregated state into some separate storage. So in case of failure, you can basically recall from that state and come back."
"It provides us the flexibility to deploy it on any cluster without being constrained by cloud-based limitations."
"Apache Flink allows you to reduce latency and process data in real-time, making it ideal for such scenarios."
"This is truly a real-time solution."
"The most valuable feature of the solution is the ability that it provides its users to handle different kinds of rules."
"There is room for improvement in the initial setup process."
"The machine learning library is not very flexible."
"Apache Flink should improve its data capability and data migration."
"The solution could be more user-friendly."
"Amazon's CloudFormation templates don't allow for direct deployment in the private subnet."
"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."
"There is a learning curve. It takes time to learn."
"PyFlink is not as fully featured as Python itself, so there are some limitations to what you can do with it."
"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.
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