Using structured data with Python

To use structured data with Python, you must choose a database for storing structured data. The Bookshelf sample app uses a structured data model for storing information about books. You can explore the sample by using one of three different backing databases: Cloud SQL, Cloud Datastore, or MongoDB.

This page is part of a multipage tutorial. To start from the beginning and read the setup instructions, go to Python Bookshelf app.

To get started with the Bookshelf tutorial, choose one of the following options:

Database Why use this option? Configuration
Cloud SQL
Managed MySQL
Use Cloud SQL >
Choose this option if you're familiar with MySQL or if you're interested in a managed relational database.

Benefits:

  • Create and configure your databases. Cloud SQL handles all other management tasks such as replication and patch management.
  • Access your data in Cloud SQL databases by using all the tools and apps already built for MySQL.
  • Use your favorite MySQL tools and apps because Cloud SQL is MySQL in the cloud.
Create a Cloud SQL instance and configure access.
Cloud Datastore
Managed NoSQL database
Use Cloud Datastore >
Choose this option if you want a zero-configuration, fully managed, highly scalable, non-relational database.

Benefits:

  • Don't worry about provisioning or load anticipation. Cloud Datastore automatically scales based on your app's users and traffic.
  • Query your data with SQL-like queries that support filtering and sorting.
No additional configuration needed.
MongoDB
Run MongoDB on Compute Engine
Use MongoDB >
Choose this option if you're familiar with MongoDB or if you want to learn how to run your own database on Compute Engine.

Benefits:

  • Deploy a MongoDB cluster on virtual machines that you provision and control. Alternatively, you can use a managed service like mLab.
  • Take advantage of the MongoDB knowledge you have.
  • Get support from MongoDB's rapidly growing community.
Deploy and configure a MongoDB cluster.
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