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Big Data Technologies that Everyone Should Know in 2024

Knowledge Hut

In the past, this data was too large and complex for traditional data processing tools to handle. However, advances in technology have now made it possible to store, process, and analyze big data quickly and effectively. Let's explore the technologies available for big data.

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NoSQL vs SQL- 4 Reasons Why NoSQL is better for Big Data applications

ProjectPro

Big Data NoSQL databases were pioneered by top internet companies like Amazon, Google, LinkedIn and Facebook to overcome the drawbacks of RDBMS. RDBMS is not always the best solution for all situations as it cannot meet the increasing growth of unstructured data.

NoSQL 49
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The Role of Database Applications in Modern Business Environments

Knowledge Hut

MongoDB): MongoDB is a prominent database software that comes under the category of "document store" databases. Document store databases, such as MongoDB, are intended to store and manage data that is unstructured or semi-structured, such as documents. Database Software- Document Store (e.g.-MongoDB):

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MongoDB and Hadoop

ProjectPro

Hadoop is the way to go for organizations that do not want to add load to their primary storage system and want to write distributed jobs that perform well. MongoDB NoSQL database is used in the big data stack for storing and retrieving one item at a time from large datasets whereas Hadoop is used for processing these large data sets.

MongoDB 40
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What Is Full Stack Web Development? A Complete 2024 Guide

Edureka

In other words, full stack developers are proficient in both the technologies that power what users see and interact within their web browsers, as well as the technologies that handle data storage, user authentication, and server-side processing behind the scenes. What Does a Full Stack Developer Do?

MongoDB 40
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Top 10 Hadoop Tools to Learn in Big Data Career 2024

Knowledge Hut

NoSQL This database management system has been designed in a way that it can store and handle huge amounts of semi-structured or unstructured data. NoSQL databases can handle node failures. Different databases have different patterns of data storage. Some databases like MongoDB have weak backup ability.

Hadoop 52
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Unstructured Data: Examples, Tools, Techniques, and Best Practices

AltexSoft

Without a fixed schema, the data can vary in structure and organization. File systems, data lakes, and Big Data processing frameworks like Hadoop and Spark are often utilized for managing and analyzing unstructured data. You can’t just keep it in SQL databases, unlike structured data.