ProjectPro

NOVEMBER 7, 2016

Understanding the Hadoop architecture now gets easier! This blog will give you an indepth insight into the architecture of hadoop and its major components- HDFS, YARN, and MapReduce. We will also look at how each component in the Hadoop ecosystem plays a significant role in making Hadoop efficient for big data processing.

Hadoop 40

Hadoop Architecture IT Big Data 40

AltexSoft

MAY 14, 2021

There are also client layers where all data management activities happen. When data is in place, it needs to be converted into the most digestible forms to get actionable results on analytical queries. For that purpose, different data processing options exist. This, in turn, makes it possible to process data in parallel.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Data Engineering Weekly

DECEMBER 21, 2022

The Rise of Data Modeling Data modeling has been one of the hot topics in Data LinkedIn. Hadoop put forward the schema-on-read strategy that leads to the disruption of data modeling techniques as we know until then. Let’s reference what the data world looked like before the Hadoop era.

Data Engineer 57

Data Engineer Data Engineering Engineering Hadoop 57

Knowledge Hut

APRIL 23, 2024

Early Challenges and Limitations in Data Handling The history of data management in big data can be traced back to manual data processing—the earliest form of data processing, which makes data handling quite painful. In 2001, Doug Laney defined big data and highlighted its features.

Big Data 52

Big Data Amazon Web Services Cloud Computing Media 52

Knowledge Hut

NOVEMBER 17, 2023

AWS has changed the life of data scientists by making all the data processing, gathering, and retrieving easy. In 2006, Amazon launched AWS to handle its online retail operations. Amazon Elastic MapReduce (EMR) helps efficiently process and analyze big data using servers like Spark and Hadoop.

AWS 52

AWS Certification Data Science Amazon Web Services 52

ProjectPro

AUGUST 31, 2018

Running services in the cloud involve data processing that needs to be saved at some time. However, Azure’s storage capabilities are also highly reliable.Both AWS and Azure are strong in this category and include all the basic features such as REST API access 3and server-side data encryption. Is Azure the same as AWS?

AWS 45

AWS Cloud Amazon Web Services Cloud Computing 45

ProjectPro

JANUARY 24, 2023

Google BigQuery Architecture- A Detailed Overview BigQuery is built on Dremel technology, which has been used internally at Google since 2006. Google's Dremel is an interactive ad-hoc query solution for analyzing read-only hierarchical data. The data processing architectures of BigQuery and Dremel are slightly similar, however.

Bytes 52

Bytes Google Cloud Data Warehouse Cloud Storage 52

ProjectPro

SEPTEMBER 6, 2021

It is a serverless data integration service that makes data preparation easier, cheaper and faster. On the other hand, GCP Dataflow is a fully managed data processing service for batch and streaming big data processing. Launched in 2006.

AWS 52

AWS Amazon Web Services Google Cloud Cloud Storage 52

ProjectPro

JULY 23, 2021

Real-time Data Processing Application 7. Real-time Data Processing Application The goal is to process the high-volume data quantities in real-time with no compromises on the accuracy of the outcomes. Ace your Big Data engineer interview by working on unique end-to-end solved Big Data Projects using Hadoop.

AWS 52

AWS Project Amazon Web Services Cloud Computing 52

AltexSoft

JULY 29, 2022

Depending on how you measure it, the answer will be 11 million newspaper pages or… just one Hadoop cluster and one tech specialist who can move 4 terabytes of textual data to a new location in 24 hours. The Hadoop toy. So the first secret to Hadoop’s success seems clear — it’s cute. What is Hadoop?

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59