1, Hadop

Hadoop was born in 2005 as a project designed by Yahoo (Yahoo) to solve the problem of web search. Due to its technical efficiency, it was later introduced as an open source application by the Apache Software Foundation.Hadoop is not a product in itself, but rather an ecosystem of software products that combine to enable comprehensive functionality and flexible big data analytics. Technically, Hadoop consists of two key services:a reliable data storage service using the Hadoop Distributed File System (HDFS) and a high-performance parallel data processing service using MapReduce technology.

2. Hive

Hive is a data warehouse architecture built on top of the Hadoop file system for analyzing and managing data stored in HDFS.Facebook was born and developed in response to the management and machine learning Facebook the need to manage and machine learn from the huge amount of new social network data generated every day. Later, other companies started using and developing Apache Hive, such as Netflix, Amazon, and others.

3. Storm

Storm is a distributed computing framework written primarily in the Clojure programming language. Founded by Nathan Marz and his team at BackType, the marketing and intelligence company was acquired by Twitter in 2011.Twitter then open-sourced the project and promoted it to GitHub.Storm was eventually added to the Apache Incubator Program in September 2014, making it officially one of the top Apache projects.

About what tools are available in the big data technology space, Green Vine has shared with you. If you have a strong interest in big data engineering, I hope this article can help you. If you still want to know more about data analysts, big data engineers tips and materials, you can click on other articles on this site to learn.