MongoDB and Python

Chapter 1. Getting Started

Introduction

First released in 2009, MongoDB is relatively new on the database scene compared to contemporary giants like Oracle which trace their first releases to the 1970’s. As a document-oriented database generally grouped into the NoSQL category, it stands out among distributed key value stores, Amazon Dynamo clones and Google BigTable reimplementations. With a focus on rich operator support and high performance Online Transaction Processing (OLTP), MongoDB is in many ways closer to MySQL than to batch-oriented databases like HBase.

The key differences between MongoDB’s document-oriented approach and a traditional relational database are:

1. MongoDB does not support joins.

2. MongoDB does not support transactions. It does have some support for atomic operations, however.

3. MongoDB schemas are flexible. Not all documents in a collection must adhere to the same schema.

1 and 2 are a direct result of the huge difficulties in making these features scale across a large distributed system while maintaining acceptable performance. They are tradeoffs made in order to allow for horizontal scalability. Although MongoDB lacks joins, it does introduce some alternative capabilites, e.g. embedding, which can be used to solve many of the same data modeling problems as joins. Of course, even if embedding doesn’t quite work, you can always perform your join in application code, by making multiple queries.

The lack of transactions can be painful at times, but fortunately MongoDB ...