What are the main characteristics of Kafka?
Kafka is a distributed streaming platform with the following key features:
- High throughput: Kafka has the capability to handle large-scale data streams and provide very high throughput. It can effectively support reading and writing operations of millions of messages per second.
- Low latency: Kafka is designed for real-time data stream processing, resulting in lower transmission delays. This makes Kafka an ideal choice for handling real-time data and suitable for applications that require timely responses.
- Horizontal scaling: Kafka utilizes a distributed architecture, making it easy to horizontally scale to meet the growing data and load demands. By adding new nodes, the processing capacity of the Kafka cluster can be expanded linearly.
- Kafka ensures durability by persisting messages to disk, ensuring that data remains reliable even in cases of consumer failures or network interruptions.
- Multiple subscriber support: Kafka enables multiple consumers to read messages from the same topic simultaneously, allowing multiple applications to independently consume the same data stream, providing greater flexibility.
- Horizontal scalability: Kafka easily integrates with other data processing systems such as Hadoop, Spark, etc., supporting various data processing and analysis scenarios.
In general, Kafka’s key features include high throughput, low latency, horizontal scalability, durability, multi-subscriber support, and horizontal scalability, making it an excellent choice for handling large-scale real-time data streams.
