Apache Storm
The Storm from Apache can be best defined as a computational framework that is made to utilize high-performance distributed systems and perform complex operations with large amounts of fed data. This open-source tool is compatible with several operating systems and is designed to deliver the best results, every time.
Top Apache Storm Alternatives
- MATLAB
- Protégé
- Sparkling Water
- DataRobot
- TensorFlow
- Gensim
- Salesforce Einstein
- OpenAI Gym
- Theano
- IBM Watson Studio
- Azure Machine Learning Studio
- Domino Data Lab
- Big Squid
- Plotly
- Amazon Personalize
Top Apache Storm Alternatives and Overview
MATLAB
MATLAB is a data science and machine learning-based development toolkit that processes iterative formulas into computer-based processes.
DataRobot
DataRobot is a reliable enterprise AI platform that allows you to automate all the processes for building, deploying, and maintaining AI at large scales.
TensorFlow
TensorFlow is an open-source library with functions that enable easy implementation of end-to-end machine learning models and datasets.
Gensim
Gensim was developed in 2008, when it served as a form of digital library where it gave results of articles that sounded similar to the searched article.
Salesforce Einstein
Using artificial intelligence and machine learning on processes, it increases customer satisfaction by switching guesswork...
OpenAI Gym
The software has been created in such a manner that it supports a wide variety...
Theano
The software program has been developed in such a way that it allows its users...
Azure Machine Learning Studio
This GUI-based integrated platform assists developers and data scientists throughout the development lifecycle and helps...
Domino Data Lab
It allows the data scientists to process a vast amount of information with its platform...
Big Squid
It offers to consult for executives and business stakeholders to make optimized decisions and reap...
Apache Storm Review and Overview
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.
Company Information
Company Name: machine-learning in Python