Perbandingan Lengkap antara Confluent dan Apache Kafka

Apache Kafka is the industry standard for organizations that are looking to become more data-driven and solve complex data streaming challenges. Real-time analytics, fraud detection, AI enablement—data streaming use cases are nearly endless. While the open source project is highly flexible, using it on its own can present a number of challenges and hidden costs.

When an organization chooses to self-manage open source Kafka, it chooses to take on the responsibilities of balancing clusters, monitoring brokers, and managing software upgrades. Additionally, it will need to solve many of the same problems that Confluent has already solved through millions of hours of focused expertise. Confluent's powerful data streaming platform can elevate any Kafka implementation to ensure that data in motion is more reliable, available and secure.

Let’s compare what you get from a self-managed Kafka solution with the added value provided by Confluent's data streaming platform.

With the Kora engine, we’ve unlocked a new way for you to experience data streaming in the cloud—with seamless scaling, uninterrupted uptime, and no operational tasks or surprises standing between you and your best work.

Confluent engineers have spent millions of hours re-architecting its streaming engine to fully manage your Kafka workloads. The end result? A cloud-native Kafka engine that abstracts away operational complexities to give you:

The Confluent data streaming platform can be deployed in any environment and in any combination of environments. To meet the demands of the data-driven organization, Confluent has optimized pricing, infrastructure, and security with an extensive set of feature-rich products that are focused on improving the quality and accessibility of your data.