Apache Kafka Technology, distributed platforms, real-time processing and Live Data to the Enterprise

The importance of real-time data in the modern enterprise is now undeniable when it comes to gain actionable value and business insights in our digital age shaped by the rapid expansion of mobile devices and applications, a growing deluge of Web application data, and the emerging Internet of Things (IoT).

 

In fact, more and more data is taking the form of real-time streams. Traditional databases and file systems are ill-equipped to handle stream data. a new class of data management infrastructure is needed to handle this imminent, critical need. Organizations are struggling to transition towards distributed platforms in general and real-time processing in particular.

Based on this reality, Connectikpeople.co recalls that, the Confluent Platform, built around Apache Kafka emphasizes the growing importance of real-time data in the modern enterprise. 

Apache Kafka helps cope with the very large-scale data ingestion and processing requirements of the business networking service.

Kafka is becoming a standard requirement of the modern data management architecture.

Developers can use this technology to build a centralized data pipeline enabling microservices or enterprise data integration, such as high-capacity ingestion routes for Apache Hadoop or traditional data warehouses, or as a foundation for advanced stream processing using Apache Spark, Storm or Samza.

Kafka is low-latency enough to satisfy real-time stream processing needs, scalable enough to handle very high volume log and event data and fault-tolerant enough for critical data delivery.