Digging into Hadoop-based Big Data Architectures
Citations Over TimeTop 10% of 2017 papers
Abstract
During the last decade, the notion of big data invades the field of information technology.This reflects the common reality that organizations have to deal with huge masses of information that need to be treated and processed, which represents a strong commercial and marketing challenge.The analysis and collection of Big Data have brought about solutions that combine traditional data warehouse technologies with the systems of Big Data in a logical and coherent structure.Thus, many vendors offer their own Hadoop distributions such as HortonWorks, Cloudera, MapR, IBM Infosphere BigInsights, Pivotal HD, Microsoft HD Insight, and so on.Their main purpose was to supply companies with a complete, stable and secure Hadoop solution for Big Data.They even compete with each other's to find efficient and complete solutions to satisfy their customers need and, hence, make benefit from this fast-growing market.In this article, we shall present a comparative study in which we shall use 34 relevant criteria to determine the advantages and drawbacks of the most outstanding Hadoop distribution providers.
Related Papers
- Big Data Mining and Semantic Technologies: Challenges and Opportunities(2015)
- Sketch of Big Data Real-Time Analytics Model(2015)
- → A Study on Big Data Analytics Tools(2023)2 cited
- → Big Data Characteristics, Challenges, Architectures, Analytics and Applications: A Review(2017)1 cited
- → Deciphering Big Data Research Themes(2018)