Jesse Anderson

DECEMBER 12, 2022

Doug Cutting took those papers and created Apache Hadoop in 2005. They were the first companies to commercialize open source big data technologies and pushed the marketing and commercialization of Hadoop. Hadoop was hard to program, and Apache Hive came along in 2010 to add SQL. They eventually merged in 2012.

Data Engineer 130

Data Engineer Data Engineering Engineering Hadoop 130

Data Engineering Weekly

DECEMBER 21, 2022

Hadoop put forward the schema-on-read strategy that leads to the disruption of data modeling techniques as we know until then. We went through a full cycle that “schema-on-read ” led to the infamous GIGO (Garbage In, Garbage Out) problem in data lakes, as noted in this What Happened To Hadoop retrospect.

Data Engineer 57

Data Engineer Data Engineering Engineering Hadoop 57

ProjectPro

NOVEMBER 24, 2014

Hadoop (Hadoop 1.0) has progressed from a more restricted processing model of batch oriented MapReduce jobs to developing specialized and interactive processing models (Hadoop 2.0). With the advent of Hadoop 2.0, In this piece of writing we provide the users an insight on the novel Hadoop 2.0 to Hadoop 2.0.

Hadoop 40

Hadoop Programming Big Data Unstructured Data 40

ProjectPro

AUGUST 26, 2015

2005 - The tiny toy elephant Hadoop was developed by Doug Cutting and Mike Cafarella to handle the big data explosion from the web. Hadoop is an open source solution for storing and processing large unstructured data sets. Hadoop is an open source solution for storing and processing large unstructured data sets.

Big Data 40

Big Data Unstructured Data Hadoop NoSQL 40

Rockset

OCTOBER 30, 2018

Hadoop and RocksDB are two examples I’ve had the privilege of working on personally. The falling price of SATA disks in the early 2000s was one major factor for the popularity of Hadoop, because it was the only software that could cobble together petabytes of these disks to provide a large-scale storage system.

Cloud 40

Cloud IT MongoDB Hadoop 40

ProjectPro

JUNE 6, 2015

Solocal has taken big data to the next stage of BI by designing a novel vision of BI with the open source distributed computing framework Hadoop. It replaced its traditional BI structure by integrating big data and Hadoop."-April In BI – there is a need to use ETL on top of Hadoop as there is not much scripting.

Business Intelligence 40

Business Intelligence Big Data BI Hadoop 40

ProjectPro

NOVEMBER 15, 2021

Apache Spark is also quite versatile, and it can run on a standalone cluster mode or Hadoop YARN , EC2, Mesos, Kubernetes, etc. You can also access data through non-relational databases such as Apache Cassandra, Apache HBase, Apache Hive, and others like the Hadoop Distributed File System. Apache CouchDB Source: idroot.us

Big Data 52

Big Data Project Metadata Programming Language 52