Kafka vs Confluent: What are the differences?
Kafka: Distributed, fault tolerant, high throughput pub-sub messaging system. Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design; Confluent: We make a stream data platform to help companies harness their high volume real-time data streams. 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.
Kafka belongs to "Message Queue" category of the tech stack, while Confluent can be primarily classified under "Stream Processing".
Some of the features offered by Kafka are:
- Written at LinkedIn in Scala
- Used by LinkedIn to offload processing of all page and other views
- Defaults to using persistence, uses OS disk cache for hot data (has higher throughput then any of the above having persistence enabled)
On the other hand, Confluent provides the following key features:
- High-performance stream data platform
- Manage and organize data from different sources.
Kafka is an open source tool with 13.2K GitHub stars and 7.01K GitHub forks. Here's a link to Kafka's open source repository on GitHub.