It is different from traditional RDBMS databases which make use of structured query language. It is a NoSQL database which means that the relational properties and other RDBMS-related properties do not apply to it. MongoDB: Another very essential and core component of big data technology in terms of storage is the MongoDB NoSQL database.
This forms one of the main core components of big data technology which was developed by the Apache software foundation in the year 2011 and is written in Java.Ģ. It can be used to store and analyze the data present in various different machines with high storage, speed, and low costs. It was designed to store and process the data in a distributed data processing environment along with commodity hardware and a simple programming execution model. This is based on map-reduce architecture and helps in the processing of batch-related jobs and process batch information. Hadoop: When it comes to big data, Hadoop is the first technology that comes into play. Let us first cover all the technologies which come under the storage umbrella.ġ. They can mainly be classified into 4 domains. Hadoop, Data Science, Statistics & others Types of Big Data Technologiesīefore starting with the list of technologies let us first see the broad classification of all these technologies.
Machine learning has become a very critical component of everyday lives and every industry and therefore managing data through big data becomes very important.
Big data technology is used to handle both real-time and batch related data. Earlier the data was being handled by normal programming languages and simple structured query language but now these systems and tools don’t seem to do much in case of big data.īig data technology is defined as the technology and a software utility that is designed for analysis, processing, and extraction of the information from a large set of extremely complex structures and large data sets which is very difficult for traditional systems to deal with. Big data technology and Hadoop is a big buzzword as it might sound. As there has been a huge increase in the data and information domain from every industry and domain, it becomes very important to establish and introduce an efficient technique that takes care of all the needs and requirements of clients and big industries which are responsible for data generation.