Apache Kafka vs. Confluent Kafka: Choosing the Right Kafka for Your Needs

When it comes to building scalable, real-time data streaming solutions, Apache Kafka and Confluent Kafka are two of the most popular choices. While they share a common foundation, they also have distinct features and offerings. In this article, we’ll explore the differences between Apache Kafka vs. Confluent Kafka, providing you with the information you need to make an informed decision.

Apache Kafka

Apache Kafka is an open-source distributed event streaming platform developed by the Apache Software Foundation. It is designed to handle high-throughput, fault-tolerant, and real-time data streams.

Key Features of Apache Kafka

  • Publish-Subscribe Model: Kafka follows a publish-subscribe model, allowing producers to send messages to topics, and consumers to subscribe to those topics for message consumption.
  • Data Durability: Kafka offers durable storage of messages, ensuring data is retained even if consumers are not immediately available.
  • Scalability: Kafka is highly scalable and capable of handling millions of messages per second across multiple brokers.
  • Fault Tolerance: Kafka replicates data across brokers for high availability and fault tolerance.
  • Low Latency: Kafka provides low-latency message delivery, making it suitable for real-time data processing.
  • Extensive Ecosystem: Kafka integrates well with various data processing frameworks, databases, and messaging systems.


Confluent Kafka

Confluent Kafka, on the other hand, is built on top of Apache Kafka and offers additional features and tools to simplify Kafka operations and enhance its capabilities.

Key Features of Confluent Kafka

  • Confluent Platform: Confluent offers the Confluent Platform, an enterprise-grade distribution of Apache Kafka that includes additional features such as the Confluent Control Center for monitoring and management.
  • Schema Registry: Confluent provides a Schema Registry for managing and evolving Avro schemas, ensuring data compatibility and governance.
  • Kafka Connect: Confluent extends Kafka with Kafka Connect, a framework for building and running connectors to various data sources and sinks.
  • KSQL: Confluent offers KSQL, a streaming SQL engine for real-time data processing and analytics.
  • Managed Kafka: Confluent Cloud provides a fully managed Kafka service, eliminating the need for users to manage their Kafka clusters.


Comparison Table

Feature Apache Kafka Confluent Kafka
Core Kafka Functionality Yes Yes
Schema Registry No Yes
Kafka Connect No Yes
Managed Kafka (Confluent Cloud) No Yes
Monitoring and Management Tools Limited Confluent Control Center
Commercial Support Limited Yes


Q1. What is the main advantage of using Confluent Kafka over Apache Kafka?

Confluent Kafka offers additional features such as the Schema Registry, Kafka Connect, KSQL, and Confluent Cloud for managed Kafka clusters, making it a compelling choice for enterprises looking for enhanced Kafka capabilities and ease of management.

Q2. Is Confluent Kafka open-source?

While Confluent Kafka builds on open-source Apache Kafka, Confluent Platform includes both open-source components and commercial features. Confluent offers both free and paid versions of their platform.

Q3. Can I migrate from Apache Kafka to Confluent Kafka?

Yes, it is possible to migrate from Apache Kafka to Confluent Kafka since Confluent Kafka maintains compatibility with the open-source Kafka API. However, it may require adjustments due to additional features and tools in Confluent.

Q4. Which one should I choose for my project: Apache Kafka or Confluent Kafka?

The choice depends on your project’s requirements. If you need core Kafka functionality, open-source Kafka may suffice. However, if you require additional features, management tools, and commercial support, Confluent Kafka is a strong option.

Both Apache Kafka and Confluent Kafka are valuable tools for building real-time data streaming solutions. Apache Kafka provides a robust foundation for event streaming, while Confluent Kafka enhances Kafka’s capabilities with additional features and tools. Your choice should align with your project’s specific needs, budget, and level of management complexity.

For more information, explore the official documentation for Apache Kafka and Confluent Kafka.

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