We performed a comparison between Amazon Kinesis and Spring Cloud Data Flow 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."Amazon Kinesis has improved our ROI."
"I have worked in companies that build tools in-house. They face scaling challenges."
"Kinesis is a fully managed program streaming application. You can manage any infrastructure. It is also scalable. Kinesis can handle any amount of data streaming and process data from hundreds, thousands of processes in every source with very low latency."
"What turns out to be most valuable is its integration with Lambda functions because you can process the data as it comes in. As soon as data comes, you'll fire a Lambda function to process a trench of data."
"The scalability is pretty good."
"The solution has the capacity to store the data anywhere from one day to a week and provides limitless storage for us."
"The feature that I've found most valuable is the replay. That is one of the most valuable in our business. We are business-to-business so replay was an important feature - being able to replay for 24 hours. That's an important feature."
"Amazon Kinesis also provides us with plenty of flexibility."
"The most valuable feature is real-time streaming."
"The most valuable features of Spring Cloud Data Flow are the simple programming model, integration, dependency Injection, and ability to do any injection. Additionally, auto-configuration is another important feature because we don't have to configure the database and or set up the boilerplate in the database in every project. The composability is good, we can create small workloads and compose them in any way we like."
"The product is very user-friendly."
"There are a lot of options in Spring Cloud. It's flexible in terms of how we can use it. It's a full infrastructure."
"Could include features that make it easier to scale."
"Kinesis can be expensive, especially when dealing with large volumes of data."
"In order to do a successful setup, the person handling the implementation needs to know the solution very well. You can't just come into it blind and with little to no experience."
"Amazon Kinesis involved a more complex setup and configuration than Azure Event Hub."
"In general, the pain point for us was that once the data gets into Kinesis there is no way for us to understand what's happening because Kinesis divides everything into shards. So if we wanted to understand what's happening with a particular shard, whether it is published or not, we could not. Even with the logs, if we want to have some kind of logging it is in the shard."
"The solution has a two-minute maximum time delay for live streaming, which could be reduced."
"The price is not much cheaper. So, there is room for improvement in the pricing."
"It would be beneficial if Amazon Kinesis provided document based support on the internet to be able to read the data from the Kinesis site."
"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."
"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."
"Spring Cloud Data Flow could improve the user interface. We can drag and drop in the application for the configuration and settings, and deploy it right from the UI, without having to run a CI/CD pipeline. However, that does not work with Kubernetes, it only works when we are working with jars as the Spring Cloud Data Flow applications."
"Some of the features, like the monitoring tools, are not very mature and are still evolving."
Amazon Kinesis is ranked 2nd in Streaming Analytics with 21 reviews while Spring Cloud Data Flow is ranked 9th in Streaming Analytics with 5 reviews. Amazon Kinesis is rated 8.0, while Spring Cloud Data Flow is rated 8.0. The top reviewer of Amazon Kinesis writes "Used for media streaming and live-streaming data". On the other hand, the top reviewer of Spring Cloud Data Flow writes "Provides ease of integration with other cloud platforms ". Amazon Kinesis is most compared with Azure Stream Analytics, Apache Flink, Amazon MSK, Confluent and PubSub+ Event Broker, whereas Spring Cloud Data Flow is most compared with Apache Flink, Google Cloud Dataflow, Apache Spark Streaming, Azure Data Factory and Informatica PowerCenter.
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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.
