What's Big Data Technology?

Big Data Technology can be described as a software utility intended to analyze Data, Process and Extract data from extremely complex and massive data set that are beyond what Traditional Data Processing Software could never handle.

We require Big Data Processing Technologies to analyze this massive amount of real-time information and draw conclusions and predictions to minimize the dangers in the future.

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Let's take an overview of the categories that we can categorize the Big Data Technologies are classified:

The types of Big Data Technologies:

Big Data Technology is mainly divided into two types:

1. Operational Big Data Technologies
2. Analytical Big Data Technologies

The first thing to note is that The Operational Big data is about the regular day-to-day data we produce. It could be online transactions, social Media, or the information from an specific Organization or other organization. You could even consider it as a type or Raw Data which is used to feed analytical Big Data Technologies. Get a better understanding of the technology through Big Data Hadoop Course. Massive Data Hadoop Course .

Some instances from operational big Data Technologies are:

First of all, The Operational Big data is about the regular day-to-day data we create. This can be online transactions, social Media, or the information from the data of a specific Organization or other organization. You could even consider it as a type of Raw Data which is used to feed analysis of Big Data Technologies.

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Some instances from operational big Data Technologies are:

• Stock marketing
• Conducting the Space missions in which every piece of information is vital.
• Forecast information for the weather.
• Medical fields where a patient's health status is assessed.

Let's take a look at the most popular Big Data Technologies being used in the IT Industries.

Top Big Data Technologies

The top big data technologies are broken down into four areas that are classified according to:

• Information Storage
• Data Mining
• Data Analytics
• Data Visualization

Let's now look at the technology that falls into each one of these categories along with their specifics and capabilities and the businesses that use them.

Let's get started by introducing Big Data Technologies in Data Storage.

The Storage of Data

Hadoop

Hadoop Framework was created to store and process data in an distributed Data Processing Environment with common hardware and a basic model of programming. It is able to store and analyze the data that is stored on different devices with speedy speeds and low costs.

The format was developed through : Apache Software Foundation in the year 2011, 10th of December.

Written in : JAVA

The current Version: Stable Version : Hadoop 3.11

Mong O D

It is the NoSQL Document Databases such as MongoDB, offer an replacement to rigid schemas that is used for Relational Databases. This lets MongoDB to be flexible as it handles a broad range of datatypes in large quantities and across distributed architectures.

Created in the year 2009 by : MongoDB in the year 2009, on the 11th of February

Written in : C++, Go, JavaScript, Python

The current Version: Stable Version : MongoDB 4.0.10

RainStor

RainStor RainStor is an software company that has developed an Database Management System of the identical name, designed to manage and analyze Big Data for large enterprises. It employs Deduplication Methods to streamline the process of storing huge quantities of data to be used as a use in.

The was developed in 2004 by : RainStor Software company in 2004.

Functions similar to the following: SQL

The current Version: Stable Version Version: RainStor 5.5

We are now ready to begin to explore Big Data Technologies used in Data Mining.

Presto is an open source Distributed SQL Query Engine that allows Interactive Analytic queries against databases of all sizes that range in size from Gigabytes up to petabytes. Presto lets you query data from Hive, Cassandra, Relational Databases as well as Proprietary Data Stores.

Created in the year 2013 by : Apache Foundation in 2013.

Written in : JAVA

Current stable version : Presto 0.22

RapidMiner RapidMiner HTML0 is an Centralized solution that has the most robust and powerful Graphical User Interface that enables users to create, deliver and maintain Predictive Analytics. It permits the creation of extremely sophisticated workflows, Scripting support for a variety of languages.

Created in the year 2001 by RapidMiner in 2001.

Written in : JAVA

The current Version: RapidMiner 9.2 stable Version : RapidMiner 9.2

Elasticsearch can be described as an Search Engine built upon the Lucene Library. It offers an Distributed MultiTenant-capable Full-Text Search Engine that includes An HTTP Web Interface as well as the ability to use Schema free JSON documents.

was developed in the year 2012 by Elastic NV 2012.

Written in : JAVA

The current version: stable Version : ElasticSearch 7.1