Understanding Basic Data Structures

Datastores rely heavily on various basic data structures. Think of these structures as the building blocks for creating and managing databases and other forms of data storage

For instance, consider relational databases like Oracle, MySQL, MSSQL, SQLite, or PostgreSQL. These databases are fundamentally structured around tables, a type of data structure. Similarly, NoSQL databases, often used in machine learning or AI applications, revolve around key-value pairs, another fundamental data structure.

In Python, lists and dictionaries are widely used data structures. A list, as you might already know, is a simple collection of items. Here is an example of a list that contains the names of different databases:

1myList = ['Oracle', 'MySQL', 'MSSQL', 'SQLite', 'PostgreSQL']

A dictionary, on the other hand, stores data as key-value pairs. It resembles the structure of a NoSQL database. Here's an example:

1myDictionary = {'key1':'value1', 'key2':'value2', 'key3':'value3'}

Understanding these basic data structures is crucial when it comes to building datastores from scratch, as it's these structures that form the foundation of how data is stored, accessed, and manipulated.

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if __name__ == "__main__":

    # Python logic here

    myList = ['Oracle', 'MySQL', 'MSSQL', 'SQLite', 'PostgreSQL']

    myDictionary = {'key1':'value1', 'key2':'value2', 'key3':'value3'}

    for i in myList:

        print('Database: ', i)

    for key, value in myDictionary.items():

        print('Key: ', key, ' Value: ', value)

    print('Understanding Basic Data Structures')