Benthos
Apache NiFi
Apache Flink
Apache Beam
Apache Airflow
Databricks
Azure Data Factory
PipeGears
Confluent
Amazon Kinesis
Apache Flink
Spark Streaming
Azure Stream Analytics
PieSync
Google Cloud Dataflow
Google Cloud Pub/Sub
Benthos ConfluentBased on our record, Benthos seems to be a lot more popular than Confluent. While we know about 23 links to Benthos, we've tracked only 1 mention of Confluent. 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.
Streaming and transforming structured documents at scale used to require some awfully complex machinery such as Apache Camel, Kafka Connect, Flink, etc. I was so happy when I bumped into Benthos https://benthos.dev which can be used as a lightweight replacement in most cases. Bonus: It’s written in Golang, so I don’t have to bother with heavy dependencies and slow start times. - Source: Hacker News / 9 days ago
If you're interested in Golang and data streaming, https://benthos.dev is a good project to contribute to. There are quite a few issues open on the GitHub project which anyone can pick up. Writing new connectors and adding tests / docs is always a good place to start. The maintainer is super-friendly and he's always active on the https://benthos.dev/community channels. I'm also there most of the time, since I've... - Source: Hacker News / 2 months ago
I have been working in the stream processing space since 2020 and I used Benthos. Since Benthos is a stateless stream processor, I have other components around it which deal with various types of application state, such as Kafka, NATS, Redis, various flavours of SQL databases, MongoDB etc. Source: about 1 year ago
You might want to add Benthos to your stack. It’s Open Source and it works great for data streaming tasks. You could have your task orchestrator (Airflow, Flyte etc) run it on demand. I demoed it at KnativeCon last year. Source: about 1 year ago
A few years ago, I found Benthos (the Open Source data streaming processor) and it was really easy to dive into it and add new features. Going through the various 3rd party libraries that it includes is usually straightforward and I'm comfortable enough with the language and various design patterns now to quickly get what's going on. That was rarely the case with C++. Source: about 1 year ago
We’re going to setup a Kafka cluster using confluent.io, create a producer and consumer as well as enhance our behavior driven tests to include the new interface. We’re going to update our helm chart so that the updates are seamless to Kubernetes and we’re going to leverage our observability stack to propagate the traces in the published messages. Source: about 2 years ago
Apache NiFi - An easy to use, powerful, and reliable system to process and distribute data.
Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Apache Beam - Apache Beam provides an advanced unified programming model to implement batch and streaming data processing jobs.
Spark Streaming - Spark Streaming makes it easy to build scalable and fault-tolerant streaming applications.
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.