Philosophy

Design Philosophy

New database technologies are needed to facilitate horizontal scaling of the data layer, easier development, and the ability to store order(s) of magnitude more data than was used in the past.

A non-relational approach is the best path to database solutions which scale horizontally to many machines.

It is unacceptable if these new technologies make writing applications harder. Writing code should be faster, easier, and more agile.

The document data model (JSON/BSON) is easy to code to, easy to manage(schemaless), and yields excellent performance by grouping relevant data together internally.

It is important to keep deep functionality to keep programming fast and simple. While some things must be left out, keep as much as possible – for example secondaries indexes, unique key constraints, atomic operations, multi-document updates.

Database technology should run anywhere, being available both for running on your own servers or VMs, and also as a cloud pay-for-what-you-use service.

Focus

MongoDB focuses on four main things: flexibility, power, speed, and ease of use. To that end, it sometimes sacrifices things like fine grained control and tuning, overly powerful functionality like MVCC that require a lot of complicated code and logic in the application layer, and certain ACID features like multi-document transactions.

Flexibility

MongoDB stores data in JSON documents (which we serialize to BSON). JSON provides us a rich data model that seamlessly maps to native programming language types, and since its schema-less, makes it much easier to evolve your data model than with a system with enforced schemas such as a RDBMS.

Power

MongoDB provides a lot of the features of a traditional RDBMS such as secondary indexes, dynamic queries, sorting, rich updates, upserts (update if document exists, insert if it doesn't), and easy aggregation. This gives you the breadth of functionality that you are used to from an RDBMS, with the flexibility and scaling capability that the non-relational model allows.

Speed/Scaling

By keeping related data together in documents, queries can be much faster than in a relational database where related data is separated into multiple tables and then needs to be joined later. MongoDB also makes it easy to scale out your database. Autosharding allows you to scale your cluster linearly by adding more machines. It is possible to increase capacity without any downtime, which is very important on the web when load can increase suddenly and bringing down the website for extended maintenance can cost your business large amounts of revenue.

Ease of use

MongoDB works hard to be very easy to install, configure, maintain, and use. To this end, MongoDB provides few configuration options, and instead tries to automatically do the "right thing" whenever possible. This means that MongoDB works right out of the box, and you can dive right into developing your application, instead of spending a lot of time fine-tuning obscure database configurations.