Artificial Intelligence Governance Professional Exam 2025 – Complete Practice Test

Hadoop is recognized for its substantial impact on data management in 2006, marking a pivotal moment in the evolution of handling large datasets. Developed by Doug Cutting and Mike Cafarella, Hadoop introduced a scalable and distributed framework for processing and storing vast amounts of data across clusters of computers. Its core components, including the Hadoop Distributed File System (HDFS) and MapReduce programming model, allowed businesses and organizations to effectively analyze and manage big data, which was becoming increasingly prominent at that time.

Hadoop’s ability to handle data that is not only large in volume but also varied in format made it a game-changer for industries looking to leverage data analytics for decision-making. This framework empowered organizations to go beyond traditional data management systems, supporting more sophisticated data processing needs.

The other software listed had notable impacts but either came to prominence later or did not significantly shift the landscape of data management in the same way as Hadoop did in 2006. For instance, MySQL has been a long-standing relational database management system but does not specifically address the challenges associated with big data. MongoDB, while influential in the NoSQL space, gained traction after Hadoop's introduction. Cassandra emerged as a distributed database that became prominent later in the 2010s,