NATS vs Kafka.
Comparison for the UNS.

Content

In the rapidly developing industrial Internet of Things (IIoT) landscape, selecting the right message protocol ensures seamless data exchange. Two prominent protocols, NATS and Kafka, offer unique features tailored to different use cases. This article explores the main differences between NATS and Kafka, particularly in implementing a Unified Namespace (UNS). It guides you in deciding which protocol best suits your requirements.

NATS vs KafkaBasics of NATS

NATS (Neural Autonomic Transport System) is an open-source, lightweight, and powerful messaging system designed to develop distributed applications. Originally developed by Derek Collison, NATS is now maintained by the Cloud Native Computing Foundation (CNCF). It is recognized as a robust enterprise service bus for the IIoT, used by startups and large enterprises alike, including e.Go, Volvo, and Schaeffler. NATS eignet sich hervorragend für hochleistungsfähige und skalierbare Umgebungen und bietet mehrere Messaging-Pattern wie Publish-Subscribe, Request-Reply und Point-to-Point-Messaging. More information can be found on the NATS website.

 

Basics of Kafka

Kafka, das von LinkedIn entwickelt und von der Apache Software Foundation als Open Source zur Verfügung gestellt wird, ist eine verteilte Streaming-Plattform, die für den Aufbau von Echtzeit-Datenpipelines und Streaming-Anwendungen konzipiert wurde. It is renowned for handling high-throughput, fault-tolerant, and low-latency data streams. It uses a publish-subscribe model, where producers send records to topics, and consumers read these records from topics. Kafka’s architecture makes it ideal for processing and analyzing large volumes of data in real-time. For more details, visit the Kafka website.

 

NATS vs Kafka: Which protocol is used for the unified namespace?

The Unified Namespace (UNS) is a data-centric architecture that simplifies data exchange between OT devices and IT applications by providing a central broker where all data is uniformly accessible. To learn more about read our guide here. This section compares NATS and Kafka in the context of UNS.

IT/OT Integration into an Unified Namespace (UNS)

 

Messaging-Pattern

Both NATS and Kafka use the publish-subscribe model. Producers send messages to topics or subjects, and consumers subscribe to these topics or subjects to receive messages. This model supports many communication patterns, such as the UNS.

 

Deployment

Kafka: Written in Java and Scala, Kafka requires JVM installation and tuning. It relies on multiple JVM processes, including Zookeeper (unless using KRaft), broker nodes, and often Kafka Streams JVMs for advanced functionalities. This complexity adds to the deployment and maintenance efforts.

NATS: Written in Go, NATS avoids JVM dependencies, consolidating all functionalities into a single nats-server binary (15MB) without additional dependencies. This design simplifies installation and management, making it easier to deploy and use.

 

Community

Kafka: Due to its wider distribution, Kafka has a larger community, which results in a high availability of libraries and connectors. This extensive support makes finding resources and solutions for various use cases easier.

NATS: NATS, while not yet a widely adopted protocol, is steadily growing. Its community is smaller but dedicated, with ongoing development and increasing use cases and integrations.

 

Resource Usage

Kafka: Kafka requires high computing power and storage, designed to handle large-scale data streams and store messages for longer durations.

NATS: NATS has low computing and storage requirements since it does not store messages by default. This lightweight approach suits scenarios with limited resources or low-latency needs.

 

Conclusion

NATS and Kafka have unique strengths, and their choice depends on your specific use case. Kafka is more suitable for big data applications by providing high-throughput, fault-tolerant data processing. NATS, on the other hand, is designed for high performance and low latency. Therefore, it is necessary to evaluate the use-case-specific requirements to select the most appropriate protocol for a unified namespace.

About i-flow: At i-flow, we are dedicated to empowering manufacturers with the world’s most intuitive software to seamlessly connect factories at scale. Over 400 million data operations daily in production-critical environments not only demonstrate the scalability of the software, but also the deep trust our customers place in i-flow. Close cooperation with our customers and partners worldwide, including renowned Fortune 500 companies and industry leaders such as Bosch, Sto and Lenze, is at the heart of our business.

Try it out now - free trial version

Experience the unlimited possibilities that i-flow offers by taking a test for yourself. Test now for 30 days free of charge on your systems.

Your question has not been answered? Contact us.

Our data policy applies.

Your Contact:

Marieke Severiens (i-flow GmbH)
content@i-flow.io