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NoSQL Data Stores - Full Stack Python

Relational databases store the vast majority of web application persistent data. However, there are several alternative classifications of storage representations.

  1. Key-value pair
  2. Document-oriented
  3. Column-family table
  4. Graph

These persistent data storage representations are commonly used to augment, rather than completely replace, relational databases. The underlying persistence type used by the NoSQL database often gives it different performance characteristics than a relational database, with better results on some types of read/writes and worse performance on others.

Key-value Pair

Key-value pair data stores are based on hash map data structures.

Key-value pair data stores Key-value pair resources Redis resources Document-oriented

A document-oriented database provides a semi-structured representation for nested data.

Document-oriented data stores Document-oriented data store resources Column-family table

A column-family table class of NoSQL data stores builds on the key-value pair type. Each key-value pair is considered a row in the store while the column family is similar to a table in the relational database model.

Column-family table data stores Graph

A graph database represents and stores data in three aspects: nodes, edges and properties.

A node is an entity, such as a person or business.

An edge is the relationship between two entities. For example, an edge could represent that a node for a person entity is an employee of a business entity.

A property represents information about nodes. For example, an entity representing a person could have a property of "female" or "male".

Graph data stores Graph data store resources NoSQL third-party services NoSQL data store resources NoSQL data stores learning checklist
  1. Understand why NoSQL data stores are better for some use cases than relational databases. In general these benefits are only seen at large scale so they may not be applicable to your web application.

  2. Integrate Redis into your project for a speed boost over slower persistent storage. Storing session data in memory is generally much faster than saving that data in a traditional relational database that uses persistent storage. Note that when memory is flushed the data goes away so anything that needs to be persistent must still be backed up to disk on a regular basis.

  3. Evaluate other use cases such as storing transient logs in a document-oriented data store such as MongoDB.

What do you want to learn about next?

Tell me about standard relational databases.

I've built a Python web app, now how do I deploy it?

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