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NoSQL Concepts

In this conceptual course (no coding required), you will learn about the four major NoSQL databases and popular engines.

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2 Hours17 Videos54 Exercises2,543 Learners
4550 XP

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Course Description

Confused about NoSQL and how it differs from SQL? You've come to the right place!

In this conceptual course (no coding required), you’ll be introduced to learn the four major NoSQL databases, including key-value, document, column family, and graph. You’ll learn about four popular NoSQL engines—including Redis, MongoDB, Apache Cassandra, and Neo4j—and when to apply them to achieve a specific business requirement. You’ll follow the data escapades of a fictional social network and learn how NoSQL can help them handle and extract insights from unstructured data like social posts. Lastly, you’ll study real use cases of when NoSQL databases were used—giving you the knowledge you need to effectively store data in any situation.

  1. 1

    Key-value databases


    To begin the course, you’ll learn the differences between NoSQL and relational databases. After that, you'll discover key-value databases, their advantages, and their limitations. You’ll recognize the situations in which key-value databases are suitable. You’ll end this chapter by studying the case of Editoo, a company that reduced its downtime and improved its performance thanks to the Redis key-value database.

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    50 xp
    NoSQL vs relational databases
    100 xp
    Keys and values
    100 xp
    Advantages and limitations of key-value databases
    50 xp
    Classifying advantages and limitations
    100 xp
    True or false?
    100 xp
    When to use key-value databases
    50 xp
    Appropriate use cases
    100 xp
    Suitable or not suitable
    100 xp
    Redis case study
    50 xp
    Redis features
    100 xp
    Redis and Editoo
    100 xp
  2. 2

    Document databases

    In this chapter, you'll learn the basics of document databases. Then, you'll identify the advantages and limitations of this kind of database, and you’ll recognize the situations in which document databases are suitable. Finally, you’ll end this chapter with the Shutterfly case study. They used the MongoDB document database to reduce latency and accelerate time to market.

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  3. 3

    Column family databases

    You'll look at column family databases, analyzing the advantages and limitations of this kind of database. You'll also study the situations where column family databases are suitable. Finally, you'll end this chapter with the case study of Bigmate, a company that used the Apache Cassandra database to handle millions of operations by concurrent users each second.

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Hadrien Lacroix


Database Design
Miriam Antona Headshot

Miriam Antona

Software Engineer

Miriam Antona has 10+ years of experience working as a Software Engineer. She is focused on analyzing, designing, and developing software applications for the Justice Administration. Miriam loves programming and experimenting with different technologies. She is passionate about databases and enjoys playing with data. She holds a Master of Science Degree in Computer Engineering.
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