Faust vs Kafka Streams: What are the differences?

Introduction

In this article, we will discuss the key differences between Faust and Kafka Streams, two popular stream processing frameworks used in building real-time applications. We will explore their unique features and functionalities to understand the advantages they offer in specific use cases.

1. Ease of Use: Faust is known for its simplicity and developer-friendly nature. It provides a high-level abstracted API that allows developers to write stream processing applications in a straightforward and intuitive manner. On the other hand, Kafka Streams offers a more low-level and traditional Java API, which requires a deeper understanding of Kafka concepts and intricacies.

2. Language Support: While Kafka Streams is primarily focused on Java, Faust supports Python and Scala along with Java. This language flexibility can be beneficial for development teams with different language preferences and skillsets, allowing them to leverage their existing knowledge and expertise.

3. Architecture: Faust operates as a standalone stream processing library that can be integrated with different message brokers, whereas Kafka Streams is an integral part of the Apache Kafka ecosystem, directly leveraging Kafka's distributed messaging system. This architectural difference provides flexibility in terms of message broker choices for Faust, while Kafka Streams offers seamless integration with Kafka infrastructure.

4. State Management: Kafka Streams provides built-in support for fault-tolerant stateful stream processing, allowing developers to maintain application state and perform complex operations on it. On the other hand, Faust offers more limited state management capabilities, making it suitable for use cases that require simple and light-weight stream processing functionality.

5. Time Semantics: Faust offers built-in support for event time processing, where events are processed based on the time they occurred rather than the order of arrival. Kafka Streams, on the other hand, primarily focuses on processing events in the order they are received, providing less flexibility in handling out-of-order events.

6. Integration with Ecosystem: Kafka Streams benefits from its tight integration with the larger Kafka ecosystem, allowing seamless integration with other Kafka components like connectors, producers, and consumers. Faust, although it can integrate with Kafka, also provides first-class integration with other message brokers and external systems, offering more flexibility in terms of deployment options and integration possibilities.

In summary, Faust and Kafka Streams have distinct differences in ease of use, language support, architecture, state management, time semantics, and integration with the wider ecosystem. Choosing the appropriate framework depends on specific requirements, developer preferences, and the existing infrastructure in place.