Rohan Paithankar

2 months ago | towardsdatascience.com | Niklas Lang |Roger Noble |Mikkel Dengsøe |Rohan Paithankar

As we have already seen with the basic components (Part 1, Part 2), the Hadoop ecosystem is constantly evolving and being optimized for new applications. As a result, various tools and technologies have developed over time that make Hadoop more powerful and even more widely applicable. As a result, it goes beyond the pure HDFS & MapReduce platform and offers, for example, SQL, as well as NoSQL queries or real-time streaming.

2 months ago | towardsdatascience.com | Niklas Lang |Roger Noble |Mikkel Dengsøe |Rohan Paithankar

Nowadays, a large amount of data is collected on the internet, which is why companies are faced with the challenge of being able to store, process, and analyze these volumes efficiently. Hadoop is an open-source framework from the Apache Software Foundation and has become one of the leading Big Data management technologies in recent years. The system enables the distributed storage and processing of data across multiple servers.