What is Kafka?
To handle a high volume of data and enables us to pass messages from one end-point to another, Apache Kafka is a distributed publish-subscribe messaging system. It is suitable for both offline and online message consumption. Basically, it designs a platform for high-end new generation distributed applications. It is an open source tool and is a part of Apache projects.
One of the best features of Kafka is, it is highly available and resilient to node failures and supports automatic recovery. This feature makes Apache Kafka ideal for communication and integration between components of large-scale data systems in real-world data systems.
Moreover, in order to prevent data loss, Kafka messages are persisted on the disk and replicated within the cluster. In addition, it is built on top of the ZooKeeper synchronization service. While it comes to real-time streaming data analysis, it can also integrate very well with Apache Storm and Spark. There are many more features of Apache Kafka.
Apache Kafka Features
Apache Kafka can handle scalability in all the four dimensions, i.e., event producers, event processors, event consumers and event connectors. In other words, Kafka scales easily without downtime.
Apache Kafka can work with a huge volume of data streams, easily.
3. Data Transformations
Apache Kafka offers provisions for deriving new data streams using the data streams from producers.
4. Fault Tolerance
Apache Kafka clusters can handle failures with the masters and databases.
Since Apache Kafka is distributed, partitioned, replicated, and fault tolerant, it is very reliable.
Apache Kafka is durable because it uses Distributed commit logs, which means messages persist on disk as fast as possible.
For both publishing and subscribing messages, Kafka has high throughput. Even if many TBs of messages are stored, it maintains stable performance.
8. Zero Downtime
Apache Kafka is very fast and guarantees zero downtime and zero data loss.