Based on our record, n8n.io should be more popular than Apache Flink. It has been mentiond 169 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I believe you can achieve that with n8n. Used in past (and still running) for some data transformation and little more. Possibly similar case what are you describing. https://n8n.io/. - Source: Hacker News / about 1 month ago
A startup, "DevOps Solutions" adopts Helm to streamline their Kubernetes deployments. You're a consultant tasked with creating a basic Helm Chart for n8n. It should be customizable for different environments using values. - Source: dev.to / 4 months ago
Https://n8n.io/, https://github.com/huginn/huginn, https://automatisch.io/, https://www.activepieces.com/ and theres a lot more... I've used n8n, node-red, and huginn (a while back), but imo n8n has been the simplest off the shelf. - Source: Hacker News / 4 months ago
n8n.io - a powerful workflow automation tool. - Source: dev.to / 6 months ago
Or other OSS projects that are similar, like https://n8n.io/. - Source: Hacker News / 8 months ago
I’ve recently started my journey with Apache Flink. As I learn certain concepts, I’d like to share them. One such "learning" is the expansion of array type columns in Flink SQL. Having used ksqlDB in a previous life, I was looking for functionality similar to the EXPLODE function to "flatten" a collection type column into a row per element of the collection. Because Flink SQL is ANSI compliant, it’s no surprise... - Source: dev.to / 17 days ago
You should let the Apache Flink team know, they mention exactly-once processing on their home page (under "correctness guarantees") and in their list of features. [0] https://flink.apache.org/ [1] https://flink.apache.org/what-is-flink/flink-applications/#building-blocks-for-streaming-applications. - Source: Hacker News / about 1 month ago
Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / about 2 months ago
Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 4 months ago
Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 6 months ago
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Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.