Arroyo vs Kafka REST
Overview
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Distributed, fault tolerant, high throughput pub-sub messaging system
Detailed Comparison
It provides a RESTful interface to a Kafka cluster. It makes it easy to produce and consume messages, view the state of the cluster, and perform administrative actions without using the native Kafka protocol or clients. Examples of use cases include reporting data to Kafka from any frontend app built in any language, ingesting messages into a stream processing framework that doesn't yet support Kafka, and scripting administrative actions. | It is a distributed stream processing engine written in Rust, designed to efficiently perform stateful computations on streams of data. |
Confluent REST Proxy for Kafka;
Easy to produce and consume messages;
View the state of the cluster | SQL and Rust pipelines;
Scales up to millions of events per second;
Stateful operations like windows and joins;
State checkpointing for fault-tolerance and recovery of pipelines |
Statistics | |
GitHub Stars 131 | GitHub Stars 4.6K |
GitHub Forks 663 | GitHub Forks 313 |
Stacks 50 | Stacks 0 |
Followers 2 | Followers 1 |
Votes 0 | Votes 0 |
Integrations | |
| No integrations available | |
What are some alternatives to Kafka REST, Arroyo?
Apache NiFi
An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.
Apache Storm
Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate.
Confluent
It is a data streaming platform based on Apache Kafka: a full-scale streaming platform, capable of not only publish-and-subscribe, but also the storage and processing of data within the stream
KSQL
KSQL is an open source streaming SQL engine for Apache Kafka. It provides a simple and completely interactive SQL interface for stream processing on Kafka; no need to write code in a programming language such as Java or Python. KSQL is open-source (Apache 2.0 licensed), distributed, scalable, reliable, and real-time.
Heron
Heron is realtime analytics platform developed by Twitter. It is the direct successor of Apache Storm, built to be backwards compatible with Storm's topology API but with a wide array of architectural improvements.
Kafka Manager
This interface makes it easier to identify topics which are unevenly distributed across the cluster or have partition leaders unevenly distributed across the cluster. It supports management of multiple clusters, preferred replica election, replica re-assignment, and topic creation. It is also great for getting a quick bird’s eye view of the cluster.
Kafka Streams
It is a client library for building applications and microservices, where the input and output data are stored in Kafka clusters. It combines the simplicity of writing and deploying standard Java and Scala applications on the client side with the benefits of Kafka's server-side cluster technology.
Kapacitor
It is a native data processing engine for InfluxDB 1.x and is an integrated component in the InfluxDB 2.0 platform. It can process both stream and batch data from InfluxDB, acting on this data in real-time via its programming language TICKscript.
Redpanda
It is a streaming platform for mission critical workloads. Kafka® compatible, No Zookeeper®, no JVM, and no code changes required. Use all your favorite open source tooling - 10x faster.
rdkafka
This gem is a modern Kafka client library for Ruby based on librdkafka. It wraps the production-ready C client using the ffi gem and targets Kafka 1.0+ and Ruby 2.3+.
