MongoDB is a document database, which means that instead of storing "rows" in "tables" like you do in a relational database, you store "documents" in "collections." Documents are basically JSON objects (technically BSON. This is to be distinguished from other NoSQL-type databases such as key-value stores (e.g. Tokyo Cabinet), column family stores (e.g. Cassandra) or column stores (e.g. MonetDB).

One major thing to keep in mind when deploying MongoDB is that it matters a lot if you are deploying in a public cloud or on dedicated server. We deployed in a public cloud. While we did get good performance compared to many other cloud vendors, the performance were of course not at par with beefy dedicated servers (but came with other benefits instead).

MongoDB’s new aggegation framework is now available in the nightly build! This post demonstrates some of its capabilities by using it to analyze chess games.

One of my favorite MongoDB tricks is the ability to use an ObjectId (the default type for MongoDB’s _id primary key) as a timestamp for when a document was created

For my Advanced Database Structures course, I have a lecture on non-relational databases. Right now, it’s a little too abstract for my tastes—we talk mainly about OLAP and MDX, but it’s hard to give concrete examples without setting up an OLAP cube. We’re somewhat constrained by our learning environment: instead of using a server for the class, students all have their own laptops upon which they install any software they need to use. We use mySQL (MAMP, really) to teach the relational part of the course. I’ve thought about using Mondrian to show and teach MDX, but I haven’t been able to come up with a lecture and lesson plan simple enough to make sense, but powerful enough to teach the core concepts.

The term “A Beginner’s Approach” reflects my self when finding a hard way out to connect Nodejs to MongoDB. There are lots of libraries available to use when connecting Nodejs to MongoDB. If you were trying to make your feet wet, and that’s what I’m doing until today, you probably want to try this approach. I can’t promise anything but at least, you will not get a headache.

When the team was formed earlier in the year, our first job was to expand our stack with MongoDB. However, we felt it would be a disservice to you, our customers, if we added a NoSQL datastore into the stack without first updating the relational databases that we support. So, we decided to pause MongoDB development to update both MySQL and PostgreSQL. As of today, MySQL 5.5 has gone into Beta, PostgreSQL 9.1 Beta is coming soon, and we plan to GA both releases in Q1 2012.

With the right indexes in place, MongoDB can use its hardware efficiently and serve your application’s queries quickly. In this article, based on chapter 7 of MongoDB in Action, author Kyle Banker talks about refining and administering indexes. You will learn how to create, build and backup MongoDB indexes.

Now that’s all well and good to get started with, but when you want to write a real application, you need to go a lot further. Well, this is still a getting started series after all, but I want to get you excited about the possibilities of working in a document-oriented way. I want to enthuse you to take this great technology and make it your own and use it as powerfully as you can to make fantastic applications.

In object-oriented development, we’re encouraged to approach code development through logical models, so that we can more readily conceptualise it in our mind. When we do this, we’re better able discern the logical operations used to interact with it and information that it would contain at different times.