Introduction to MongoDB

MongoDB is a popular NoSQL datastore that provides a high-performance, scalable, and flexible data storage solution for various applications. It stores data in Binary JSON (BSON) format, providing a binary representation where more type-primitives are supported, making it easy to store and process large sets of data. It is highly suited for applications that require large data processing such as finance and AI.

Compared to SQL databases, MongoDB is schema-less, meaning that documents in the same collection can have different structures. This flexibility can greatly speed up development process in scenarios where data structure can change over time.

The Python script below demonstrates basic interaction with MongoDB. We connect to a MongoDB server, create a new collection, insert a document, and query the document by one of its fields.

Referencing the code block, you can see how MongoDB makes use of the BSON format to integrate natural to programming languages. We only needed a simple dictionary to represent a complex structure that would have required creating a table schema in traditional SQL. The code demonstrates the flexibility and ease of use that MongoDB provides, making it a good fit for modern, agile software development.

In the following screens, we will deep dive into MongoDB and how we can leverage it in building data stores.

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if __name__ == '__main__':

  from pymongo import MongoClient

  # create a connection to MongoDB

  client = MongoClient('localhost', 27017)

  db = client['python-db']

  # create a new collection

  collection = db['python-collection']

  # insert a document

  collection.insert_one({'name': 'John', 'age': 30, 'profession': 'Engineer'})

  # query the document

  q_res = collection.find_one({'name': 'John'})

  print(q_res)