10gen

MongoDB Boulder transformed the Boulder Marriott into a hive of MongoDB passion and learning, attracting over 220 attendees from around the region.

Representing 10gen was President Max Schireson as well as software engineer Dan Crosta, Robert Stam, Kyle Banker (author of MongoDB in Action) and Ryan Nitz. Max kicked off and concluded the day, providing an overview of MongoDB and latest developments, as well as a vision for the platform’s future.

MongoDB Boulder also featured guest speakers including Chris Merz (MapMyFITNESS), Nathan Wells (Adaptive Computing), and David Blado (OpenShift).

Covering a range of MongoDB topics from how and when to scale MongoDB with sharding to developing iPhone and Android applications with MongoDB backends for the cloud, MongoDB Boulder imparted on attendees concrete lessons to better manage their MongoDB deployment.

Miss MongoDB Boulder this year or want to relive the glory? Keep an eye out for videos and presentations from the conference which will be posted on our site shortly.

Huge thanks to all our speakers and attendees - see you next year, Boulder!

Join us on February 9th to learn monitoring best practices for MongoDB from 10gen engineer Jared Rosoff. The webinar will include some tips and tricks for monitoring, as well as a demo of 10gen’s MongoDB Monitoring Service (MMS). MMS is a free, cloud-based monitoring and alerting solution for all MongoDB deployments. After a minimal setup and configuration, MMS produces charts, custom dashboards, and automated alerting that allows your team to manage and optimize your MongoDB deployment.

Jared Rosoff is the Director of Product Marketing at 10gen. Previously, Jared ran Product Development at Yottaa where he developed a real-time analytics engine on top of MongoDB and Ruby on Rails.

Click here to learn more about the event and register.

Shutterfly, a leading Internet-based social expression and personal publishing service, safeguards more than six billion images for millions of customers. As the only photo sharing site that does not down-sample, compress, or force delete photos, Shutterfly faced massive data growth that pushed the performance limits of its existing Oracle database. After an extensive analysis of open source relational and non-relational alternatives, Shutterfly chose MongoDB as its persistent data store.

Before implementation of MongoDB, Shutterfly stored its more than 20 TB of photo metadata in an Oracle RDBMS, vertically partitioning the data by function. The complex infrastructure became hard to manage after a decade of development and made development of new features difficult to execute quickly or correctly. The situation was further exacerbated by the the high costs associated with licensing and hardware. These challenges compelled the Shutterfly team to look at open source options that would also provide improved performance and a simpler API at a reduced cost.

Shutterfly chose MongoDB as its new storage solution primarily because the data model matched common use cases. The rich JSON-based data structure was easy for the development team to use, reduced time to market for new features, and could be leveraged for many different projects. In addition, Shutterfly saw significant performance improvements with the more natural data model. Finally, the MongoDB solution was cost-efficient, providing an open source solution that would enable them to scale horizontally across commodity hardware.

Shutterfly’s migration to MongoDB resulted in a 900% performance improvement when compared to their previous Oracle implementation. In terms of cost, Shutterfly realized a 500% reduction in moving from Oracle to MongoDB. Overall, MongoDB provided Shutterfly with a high performance solution at a significantly reduced cost.

To learn more, read the full case study, or for more resources, check out Shutterfly’s Kenny Gorman’s presentation at MongoSV 2010 “Sharing Life’s Joy using MongoDB: A Shutterfly Case Study” or the follow-up Q&A with Gorman hosted by NoSQLDatabases.com. More recently, at MongoSF 2011 Gorman presented on “MongoDB Profiling and Tuning.”