Summary
In this chapter, we looked at various ways to manage data using MongoDB. We utilized MongoDB to store non-relational data for our online book reselling system since we expect the data to become large when information is exchanged between the book buyers and resellers. Additionally, the details involved in the transactions are mainly strings, floats, and integers, which are all order and purchase values that will be easier to mine and analyze if they’re stored in schema-less storage.
This chapter took the non-relational data management roadmap for utilizing the data in sales forecasting, regression analysis of book readers’ demands, and other descriptive data analysis forms.
First, you learned how the PyMongo and Motor drivers connect the FastAPI application to the MongoDB database. After understanding the nuts and bolts of creating CRUD transactions using these drivers, you learned that ODM is the better option for pursuing MongoDB connectivity. We explored...