MongoDB: Articles and Videos

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mongodb

Getting a decent internet connection was a challenge this week, so I’ve decided that in the short time I’ve found one that worked I should share the list of articles and videos on MongoDB that I’ve had around. I’m trying to do the same with the other NoSQL projects covered on myNoSQL.

Articles

Gleicon Moraes: ☞ MongoDB and Redis for an URL shortener

I’ve wanted to prototype an URL shortener some time ago to have a measure on how long it would take to do using a NoSQL DB to store stats and do analytics. The main reason would do it using cyclone and MongoDB, and later build over it to create a tracker, web analytics tool and maybe a NGINX module.

Anthony: ☞ MongoWave: Persistence on Google FedOne Wave Server with mongoDB

As part of that effort I have been quite involved with the Google Wave Protocol project. I wanted to share my preliminary success implementing persistence on FedOne with MongoDB.

Rob Conery: ☞ Using Mongo With LINQ

Lately I’ve been working with Mongo, creating a C# driver with Karl Seguin and Andrew Theken (and James Avery and Jason Alexander) and today I checked in some optimizations that made me really stoked and I thought I would share. In short – I think we have a roundly working (but young) Linq provider for MongoDB.

BoardTracker: ☞ MySQL vs MongoDB

BoardTracker uses a distributed cluster for storing posts data. This cluster is based on MySQL, but does not use MySQL native clustering but rather our own clustering mechanism. While we will not go into details in this post about how the cluster is set up, what we will go into is the notion of MySQL vs. NoSQL in terms of performance, or more specifically comparing MySQL with MongoDB.

Daniel Huckstep: ☞ Super MongoDB MapReduce Max Out!

I’ve been playing with MongoDB lately, and I must say, it’s the shit. […] I’m going to talk about the MapReduce part of things.

Ian Warshak: ☞ Faceted search with MongoDB

Having recently worked on a project that relied heavily relied on a faceted search capability, and my desire to explore MongoDB more, I wrote a simple faceted search mechanism using MongoDBs map/reduce functionality

MongoDB Blog: ☞ On Distributed Consistency series

For distributed databases, consistency models are a topic of huge importance. We’d like to delve a bit deeper on this topic with a series of articles, discussing subjects such as what model is right for a particular use case.

Scott Watermasysk: ☞ MongoDB and C# Dynamics

There is a good C# driver called, MongoDB-CSharp. Unfortunately, because of the strongly typed nature of C#, the default implementation requires you to work with your data as a dictionary. This has an unfortunate side effect of some ugly code and a quite a bit of casting.

Mookid on Code: ☞ Even more checking out MongoDB: The coolness continues

One thing I started to think about after having looked at MongoDB was how to model things that are somehow connected – without the use of foreign keys and the ability to join stuff.

A GTA fan’s Blog: ☞ Part1 – Learning & Sharing Series – MongoDB -java

This document is to share some info collected from web and few features i tried out.

Codaset: ☞ The awesomeness that is MongoDB and NoSQL, is taking over Codaset

So after reading some really interesting and very intriguing posts by John Nunemaker about a NoSQL database called MongoDB, I began shopping around for possible solutions to cleaning up events, and making them easier to work with. Needless to say, the NoSQL movement is pretty active at the moment, but I kept coming back to MongoDB.

Codes Not Dead: ☞ MongoDB geospatial examples in Ruby

I’ve spent some time lately dabbling with the Android geolocation API and storing the results in MongoDB. It is mostly longitude/latitude values. I wanted to start doing location-based queries and I thought I had a real challenge on my hands. It was about that same time that MongoDB announced geospatial indexing and that has made things much easier. I’ve stuck some Ruby examples on github which I’ll walk through here.