Top Apache Storm Alternatives

The introduction of machine learning to the world has necessitated the enhancement of computational technology, from both speed and performance point of view. Powerful hardware is incomplete without the appropriate software being able to harness its power to the fullest degree, and that is where the Storm comes in. Apache Storm is a framework that works with speed and efficiency through its stream processing capabilities.

Powerful processing for powerful applications

The Apache Storm allows systems to process data with a method very similar to parallel processing, which means that the speed of analysis and operation of even big data clusters can be done accurately in a few seconds. This is exactly the speed that is required for mass-used cloud applications or platforms to deliver results in real-time. Additionally, it offers its users an exceptional ability to code in any language they require to use for their application. This has made it a popular choice for a great many types of developers who create applications that require delivering real-time results.

How does the Storm deliver such exceptional speeds?

The astonishing speed of deliveries commonly associated with the Apache Storm is mainly due to its processing method. It uses a unique, distributed methodology of stream processing that utilizes all the systems connected to process data at extreme speeds. Its processing topology can be likened to Hadoop’s MapReduce, but it differs in its processing method; unlike MapReduce’s batch processing, Storm processes its data streams simultaneously using several systems, i.e. by distributed computation. This exceptional speed, thus, is accompanied by less requirement of costly computational hardware as a distributed system of small clusters does the work.  

Quick data processing makes every job easier

The Apache Storm has a variety of use cases and is preferred by all due to its high-performance and programming language flexibility. Additionally, since it uses a cluster-based system, it is highly scalable in nature, so gone are the days when even smaller applications would require the purchase of costly computers. Enterprise use cases of the platform include prevention of data breaches and fraud attempts, automated operations and proper data delivery for integrations.