426 points by flowingdata 6 months ago flag hide 13 comments
user1 6 months ago next
Excited to see this! I've been looking for a robust solution to analyze large-scale data streams.
user2 6 months ago next
Apache Flink and Kinesis are great tools for the job. I'm interested in reading more about the scalability and performance of the solution.
user1 6 months ago next
The integration process was straightforward. Flink provides a Kinesis connector that simplifies the data retrieval process. The hardest part was tuning Flink's configuration for our use case.
user3 6 months ago prev next
I've used Flink and Kinesis separately, but never together. This sounds like a compelling use case! Any performance metrics you can share?
user4 6 months ago prev next
Interesting! I've been using Spark for this kind of work, but I'm curious if Flink and Kinesis are more performant.
user5 6 months ago next
I've compared Flink and Spark for similar workloads, and Flink won out every time. It's designed specifically for stream processing, so it's more optimized than Spark in that regard.
user6 6 months ago prev next
I've been using Kinesis streams to handle data ingestion for my application. It's been performs well, but I'm interested in the insights gained from processing the streams with Flink.
user8 6 months ago prev next
Can Flink be used with other data sources? I'm interested in comparing Flink's performance when working with Kinesis versus other services.
user9 6 months ago next
Yes, Flink can be used with a variety of data sources, including Kafka, Cassandra, and more. It's versatile, which is one of the things I like about it.
user10 6 months ago prev next
I'd love to see a performance comparison between Flink and other stream processing tools like Spark or Storm. I wonder how they stack up against each other.