StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. Utilities
  3. Background Jobs
  4. Kafka Tools
  5. Arroyo vs RSKafka

Arroyo vs RSKafka

OverviewComparisonAlternatives

Overview

RSKafka
RSKafka
Stacks0
Followers0
Votes0
GitHub Stars318
Forks43
Arroyo
Arroyo
Stacks0
Followers1
Votes0
GitHub Stars4.6K
Forks313

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Detailed Comparison

RSKafka
RSKafka
Arroyo
Arroyo

It aims to be a minimal Kafka implementation for simple workloads that wish to use Kafka as a distributed write-ahead log. It is not a general-purpose Kafka implementation, instead, it is heavily optimised for simplicity, both in terms of implementation and its emergent operational characteristics.

It is a distributed stream processing engine written in Rust, designed to efficiently perform stateful computations on streams of data.

Supports compression and decompression of messages; Allow transport via SOCKS5 proxy; Allows TLS transport via rustls; Exposes some internal data structures so that they can be used by our fuzzers
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
318
GitHub Stars
4.6K
GitHub Forks
43
GitHub Forks
313
Stacks
0
Stacks
0
Followers
0
Followers
1
Votes
0
Votes
0
Integrations
Rust
Rust
Kafka
Kafka
Redpanda
Redpanda
Docker
Docker
SQL
SQL
Linux
Linux
macOS
macOS
Rust
Rust
Kafka
Kafka

What are some alternatives to RSKafka, Arroyo?

Apache NiFi

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

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

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

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

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

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

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.

Kafka REST

Kafka REST

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.

Kapacitor

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

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.

Related Comparisons

Bootstrap
Materialize

Bootstrap vs Materialize

Laravel
Django

Django vs Laravel vs Node.js

Bootstrap
Foundation

Bootstrap vs Foundation vs Material UI

Node.js
Spring Boot

Node.js vs Spring-Boot

Liquibase
Flyway

Flyway vs Liquibase