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Apache Kafka Vs. Apache Storm

Apache Storm

It is an open-source and real-time stream processing system. Apache Storm was mainly used for fastening the traditional processes. It reliably processes the unbounded streams. It has spouts and bolts for designing the storm applications in the form of topology. Any pr ogramming language can use it. Thus, it is simple to use. It can process millions of messages within a second.

Kafka Vs. Storm

Apache Kafka vs Apache Storm

There are the following differences between Kafka and Storm:

Parameters Apache Kafka Apache Storm
Developers Originally developed by LinkedIn. Then, it was donated to Apache Foundation. Originally created by Nathan Marz (Backtype team). Later, acquired by Twitter. Further, it became the top-level project of Apache.
Programming Language Apache Kafka is written in Scala with JVM. Apache Storm is written in Clojure and Java.
Type of system It is a distributed messaging system. It is a real-time message processing system.
Primarily used for It is used as a message broker. But, it also does small-batch processing. It is used for micro-batch stream processing.
Data Storage It maintains the local file system, such as XFS or EXT4, for storing the data. It does not store the data. It transfers the data from the input stream to the output stream.
Depends on Apache Kafka depends on the zookeeper to run the Kafka server and let the consumer/producer to read/write the messages to Kafka. Apache Storm has no external dependency.
Latency The latency power of Kafka is millisecond. It has a latency power of less than 1-2 seconds. It is because it depends on the data source.
Language Support Best supported by Java programming language. It supports all programming languages.
Security Data is not highly secure. Data is highly secured.
Data source It takes data from the actual data sources such as facebook, twitter, etc. It fetches data from the Kafka itself for processing.
Fault-tolerant Due to zookeeper, it is able to tolerate the faults. It has an in-built feature of auto-restarting.
Developers Experience It is durable, scalable, as well as gives high-throughput value. It is easy and flexible to use.





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