Query, Analyze and Visualize Big Data With Minimal Cost - Build Hadoop on Cloud Architecture

Hadoop is an open-source plan from Apache that has grown swiftly into an influential technology evolution. It has developed as the best way to manage large volumes of data, including structured data and complicated, unstructured data. Its repute is due in part to its capacity to store, analyze and obtain large amounts of data, quickly and cost-effectively over clusters of commodity hardware.

Apache Hadoop

Apache Hadoop is not really a separate product rather a combination of many elements including the following


A framework for coding applications that treat large measures of structured and unstructured data in resemblance across huge clusters of machines in a very secure and fault-tolerant way.

Hadoop Distributed File System (HDFS)

A safe and distributed Java-based file system that enables large volumes of data to be collected and quickly reached across large clusters of commodity servers.


Developed on the MapReduce framework, Hive is a data warehouse that allows easy data summarization and ad-hoc queries via an SQL-like interface for massive datasets stored in HDFS.


A platform for processing and investigating large data sets. Pig contains a high-level language called Pig Latin for expressing data analysis programs matched with the MapReduce framework for processing those programs.


A column-oriented NoSQL data storage method that contributes random real-time read/write passage to big data for user applications.


A metadata management service and table that presents a centralized method for data processing systems to recognise the structure and location of the data stored within Apache Hadoop.

Apache Hadoop is usually not a straight replacement for company data warehouses, data stores and others that are generally employed to manage structured or transactional data. Rather, it is applied to expand enterprise data architectures by implementing an effective and cost-efficient means for collecting, processing, managing and interpreting the rising volumes of semi-structured or unstructured data being generated every day.

Apache Hadoop can be beneficial over a variety of applications over virtually all vertical industry. It is growing popular everywhere that you need to stock, process, and interpret huge volumes of data. Models include fraud disclosure and blocking, digital marketing automation, social network and relationship study, predictive modelling for latest drugs, retail in-store behaviour examination, and mobile device location-based marketing.

Apache Hadoop is broadly deployed at companies universally, including many of leading Internet and social networking companies.


A profoundly accessible system for organising distributed processes. Distributed applications use ZooKeeper to save and mediate updates to critical configuration information.


An open source installation lifecycle control, administration and monitoring method for Apache Hadoop clusters.

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