Hadoop vs MSSQL: What are the differences?
Developers describe Hadoop as "Open-source software for reliable, scalable, distributed computing". The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. On the other hand, MSSQL is detailed as "It is an enterprise-level database system that is very popular for Windows web servers". It is capable of storing any type of data that you want. It will let you quickly store and retrieve information and multiple web site visitors can use it at one time.
Hadoop and MSSQL belong to "Databases" category of the tech stack.
Hadoop is an open source tool with 9.4K GitHub stars and 5.85K GitHub forks. Here's a link to Hadoop's open source repository on GitHub.
Airbnb, Uber Technologies, and Netflix are some of the popular companies that use Hadoop, whereas MSSQL is used by esportshub, Shared User Management System - Georgia Institute of Technology, and engel80. Hadoop has a broader approval, being mentioned in 309 company stacks & 623 developers stacks; compared to MSSQL, which is listed in 20 company stacks and 22 developer stacks.
What is Hadoop?
What is MSSQL?
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Why do developers choose MSSQL?
What are the cons of using Hadoop?
What are the cons of using MSSQL?
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The MapReduce workflow starts to process experiment data nightly when data of the previous day is copied over from Kafka. At this time, all the raw log requests are transformed into meaningful experiment results and in-depth analysis. To populate experiment data for the dashboard, we have around 50 jobs running to do all the calculations and transforms of data.
in 2009 we open sourced mrjob, which allows any engineer to write a MapReduce job without contending for resources. We’re only limited by the amount of machines in an Amazon data center (which is an issue we’ve rarely encountered).
The massive volume of discovery data that powers Pinterest and enables people to save Pins, create boards and follow other users, is generated through daily Hadoop jobs...
Importing/Exporting data, interpreting results. Possible integration with SAS