Reactive-kafka alternatives and similar packages
Based on the "Big Data" category.
Alternatively, view Reactive-kafka alternatives based on common mentions on social networks and blogs.
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Deeplearning4J
Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learn... -
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Scoozie
DISCONTINUED. Scala DSL on top of Oozie XML [GET https://api.github.com/repos/klout/scoozie: 404 - Not Found // See: https://docs.github.com/rest/repos/repos#get-a-repository] -
Schemer
Schema registry for CSV, TSV, JSON, AVRO and Parquet schema. Supports schema inference and GraphQL API. -
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GridScale
Scala library for accessing various file, batch systems, job schedulers and grid middlewares. -
Spark Utils
Basic framework utilities to quickly start writing production ready Apache Spark applications -
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InfluxDB – Built for High-Performance Time Series Workloads
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
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README
Alpakka Kafka 
Systems don't come alone. In the modern world of microservices and cloud deployment, new components must interact with legacy systems, making integration an important key to success. Reactive Streams give us a technology-independent tool to let these heterogeneous systems communicate without overwhelming each other.
The Alpakka project is an open source initiative to implement stream-aware, reactive, integration pipelines for Java and Scala. It is built on top of Akka Streams, and has been designed from the ground up to understand streaming natively and provide a DSL for reactive and stream-oriented programming, with built-in support for backpressure. Akka Streams is a Reactive Streams and JDK 9+ java.util.concurrent.Flow-compliant implementation and therefore fully interoperable with other implementations.
This repository contains the sources for the Alpakka Kafka connector. Which lets you connect Apache Kafka to Akka Streams. It was formerly known as Akka Streams Kafka and even Reactive Kafka.
Akka Stream connectors to other technologies are listed in the Alpakka repository.
Documentation
Alpakka reference documentation
Alpakka Kafka connector reference documentation
To keep up with the latest Alpakka releases check out Alpakka releases and Alpakka Kafka releases.
Community
You can join these groups and chats to discuss and ask Akka and Alpakka related questions:
- Forums: discuss.lightbend.com
- Issue tracker:
In addition to that, you may enjoy following:
- The Akka Team Blog
- @akkateam on Twitter
- Questions tagged #alpakka on StackOverflow
- Questions tagged #alpakka on StackOverflow
The Kafka connector was originally created as Reactive Kafka by .
Contributing
Lightbend is the steward of Akka and Alpakka.
Contributions are very welcome! Lightbend appreciates community contributions by both those new to Alpakka and those more experienced.
Alpakka depends on the community to keep up with the ever-growing number of technologies with which to integrate. Please step up and share the successful Akka Stream integrations you implement with the Alpakka community.
If you find an issue that you'd like to see fixed, the quickest way to make that happen is to implement the fix and submit a pull request.
Refer to the [CONTRIBUTING.md](CONTRIBUTING.md) file for more details about the workflow, and general hints on how to prepare your pull request.
You can also ask for clarifications or guidance in GitHub issues directly.
Caveat Emptor
Alpakka components are not always binary compatible between releases. API changes that are not backward compatible might be introduced as we refine and simplify based on your feedback. A module may be dropped in any release without prior deprecation.
Support for the Alpakka Kafka connector is available via Lightbend's Akka Platform subscription.