We performed a comparison between Amazon MSK and Apache Flink based on real PeerSpot user reviews.
Find out in this report how the two Streaming Analytics solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Overall, it is very cost-effective based on the workflow."
"Amazon MSK has significantly improved our organization by building seamless integration between systems."
"MSK has a private network that's an out-of-box feature."
"The most valuable feature of Amazon MSK is the integration."
"It offers good stability."
"It is a stable product."
"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."
"Allows us to process batch data, stream to real-time and build pipelines."
"It provides us the flexibility to deploy it on any cluster without being constrained by cloud-based limitations."
"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 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."
"It is user-friendly and the reporting is good."
"It would be really helpful if Amazon MSK could provide a single installation that covers all the servers."
"Amazon MSK could improve on the features they offer. They are still lagging behind Confluence."
"It does not autoscale. Because if you do keep it manually when you add a note to the cluster and then you register it, then it is scalable, but the fact that you have to go and do it, I think, makes it, again, a bit of some operational overhead when managing the cluster."
"It should be more flexible, integration-wise."
"The configuration seems a little complex and the documentation on the product is not available."
"The product's schema support needs enhancement. It will help enhance integration with many kinds of languages of programming languages, especially for environments using languages like .NET."
"There is room for improvement in the initial setup process."
"In terms of improvement, there should be better reporting. You can integrate with reporting solutions but Flink doesn't offer it themselves."
"Apache Flink's documentation should be available in more languages."
"One way to improve Flink would be to enhance integration between different ecosystems. For example, there could be more integration with other big data vendors and platforms similar in scope to how Apache Flink works with Cloudera. Apache Flink is a part of the same ecosystem as Cloudera, and for batch processing it's actually very useful but for real-time processing there could be more development with regards to the big data capabilities amongst the various ecosystems out there."
"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."
"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."
"In a future release, they could improve on making the error descriptions more clear."
Amazon MSK is ranked 6th in Streaming Analytics with 6 reviews while Apache Flink is ranked 5th in Streaming Analytics with 15 reviews. Amazon MSK is rated 7.2, while Apache Flink is rated 7.6. The top reviewer of Amazon MSK writes "Efficient real-time transaction tracking but time-consuming installation". On the other hand, the top reviewer of Apache Flink writes "A great solution with an intricate system and allows for batch data processing". Amazon MSK is most compared with Confluent, Amazon Kinesis, Azure Stream Analytics, Google Cloud Dataflow and Apache Pulsar, whereas Apache Flink is most compared with Amazon Kinesis, Spring Cloud Data Flow, Databricks, Azure Stream Analytics and IBM Streams. See our Amazon MSK vs. Apache Flink report.
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