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."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."
"The documentation is very good."
"This is truly a real-time solution."
"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 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 setup was not too difficult."
"Allows us to process batch data, stream to real-time and build pipelines."
"The most valuable feature of the solution is the ability that it provides its users to handle different kinds of rules."
"In terms of improvement, there should be better reporting. You can integrate with reporting solutions but Flink doesn't offer it themselves."
"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."
"Amazon's CloudFormation templates don't allow for direct deployment in the private subnet."
"There is room for improvement in the initial setup process."
"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 a learning curve. It takes time to learn."
"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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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.
