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."Amazon MSK has significantly improved our organization by building seamless integration between systems."
"It offers good stability."
"It is a stable product."
"MSK has a private network that's an out-of-box feature."
"Amazon MSK has good integration because our team has been undergoing significant changes. Coupling it with MSK within AWS is helpful. We don't have to set up additionals or monitor external environments. This"
"Overall, it is very cost-effective based on the workflow."
"The most valuable feature of Amazon MSK is the integration."
"Allows us to process batch data, stream to real-time and build pipelines."
"It is user-friendly and the reporting is good."
"It provides us the flexibility to deploy it on any cluster without being constrained by cloud-based limitations."
"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."
"Apache Flink allows you to reduce latency and process data in real-time, making it ideal for such scenarios."
"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."
"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."
"It would be really helpful if Amazon MSK could provide a single installation that covers all the servers."
"The configuration seems a little complex and the documentation on the product is not available."
"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."
"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."
"It should be more flexible, integration-wise."
"Amazon MSK could improve on the features they offer. They are still lagging behind Confluence."
"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."
"PyFlink is not as fully featured as Python itself, so there are some limitations to what you can do with it."
"The machine learning library is not very flexible."
"Amazon's CloudFormation templates don't allow for direct deployment in the private subnet."
"Apache Flink should improve its data capability and data migration."
"There is room for improvement in the initial setup process."
"In a future release, they could improve on making the error descriptions more clear."
"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."
Amazon MSK is ranked 6th in Streaming Analytics with 7 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 "Streamlines our processes, and we don't need to configure any VPCs; it's automatic". 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, Azure Stream Analytics, Amazon Kinesis, Google Cloud Dataflow and Aiven for Apache Kafka, whereas Apache Flink is most compared with Spring Cloud Data Flow, Amazon Kinesis, Databricks, Azure Stream Analytics and Apache Spark Streaming. See our Amazon MSK vs. Apache Flink report.
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