Apache Kafka is the most popular Open-Source, Stream-processing platform, with high throughput, low latency, and fault tolerance. Let’s have a look at some of these powerful features:

Fault-Tolerant & Durable: By distributing partitions and replicating data over several servers, Kafka protects data from server failure and makes it fault-tolerant. It has the ability to restart the server by itself.

Highly Scalable with Low Latency: Kafka’s partitioned log model distributes data over several servers, allowing it to extend beyond the capabilities of a single server. Kafka has low latency and great throughput since it separates data streams.

Robust Integrations: Kafka supports various third-party integrations. It also offers many APIs. Hence, you can add more features in a matter of seconds. Take a look at how you can use Kafka with Amazon Redshift, Cassandra, and Spark.

Detailed Analysis: For tracking operational data, Kafka is a popular solution. It enables you to collect data from several platforms in real-time and organize it into consolidated feeds while keeping a check with metrics. Refer to the Real-time Reporting with Kafka Analytics article for further information on how to analyze your data in Kafka.

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