Coding With Fun
Home Docker Django Node.js Articles Python pip guide FAQ Policy

What is the difference between apache kafka and apache storm?


Asked by Briar Costa on Nov 29, 2021 Storm getting Started



Apache Kafka use to handle a big amount of data in the fraction of seconds. It is a distributed message broker which relies on topics and partitions. Apache Storm is a fault-tolerant, distributed framework for real-time computation and processing data streams.
Thereof,
Apache Kafka is a distributed data store optimized for ingesting and processing streaming data in real-time. Streaming data is data that is continuously generated by thousands of data sources, which typically send the data records in simultaneously.
Consequently, Apache Storm is the stream processing engine for processing real time streaming data while Apache Spark is general purpose computing engine which provides Spark streaming having capability to handle streaming data to process them in near real-time.
Indeed,
In this chapter, we will learn how to integrate Kafka with Apache Storm. Storm was originally created by Nathan Marz and team at BackType. In a short time, Apache Storm became a standard for distributed real-time processing system that allows you to process a huge volume of data.
Likewise,
Kafka’s out-of-the-box Connect interface integrates with hundreds of event sources and event sinks including Postgres, JMS, Elasticsearch, AWS S3, and more. Read, write, and process streams of events in a vast array of programming languages. Large ecosystem of open source tools: Leverage a vast array of community-driven tooling.