3 results

AOL's targeted advertising business: Powered by MongoDB

While AOL may evoke thoughts of dial-up broadband for some, the company today drives over $2 billion in annual revenues connecting advertisers to consumers of its premium content, including Huffington Post, Moviefone, Engadget, TechCrunch, Patch, and Stylelist. MongoDB provides the data infrastructure for a significant portion of AOL’s business, both on the content and advertising sides of AOL. In the words of Jonathan Reed , formerly a senior software engineer at AOL, “AOL uses MongoDB a lot throughout our business,” and for very different use cases. As of June 2012 AOL had over 30 MongoDB projects running internally across over 500 servers. One of the important projects for which AOL uses MongoDB is advertising, as detailed in the video above. AOL’s platform helps advertisers reach highly-targeted audiences at scale, and MongoDB plays an essential role in storing’s user profiles. AOL turned to MongoDB for its flexible data model, as user profiles have various sizes and shapes, with different kinds of information stored for different users. One key feature that MongoDB offers is geospatial indexing, which enables AOL to advertise services based on a user’s location (e.g., showing airfare pricing based on the airport nearest to the user, even if all they’ve expressed is interest in flying to Paris). Importantly, all of this must be done in under five milliseconds, which means that AOL simply can’t afford to hit disk and must keep everything in RAM. MongoDB handles this easily, processing 12,000 transactions per second, or several billion each month. MongoDB’s performance was so good, as Reed describes, the company needed a special set-up to manage network traffic, which couldn’t keep up with MongoDB. While this seems like it must require a complex set-up, Reed suggests that MongoDB is “surprisingly simple” to set up and run. In the case of for this project, MongoDB runs in a single cluster spanning three data centers, two in the U.S. and one in Europe. Indeed, ease of use was one of the top-four reasons AOL chose MongoDB to power Easy to learn and set up Easy to scale Great community Support contract available (“really good value for money”) None of this would matter, however, if MongoDB couldn’t handle AOL’s core requirement: dynamic data schema. AOL’s must constantly tweak the kind of user information it collects and stores, and has to be able to do so with super-high performance at scale. MongoDB ticks each of these boxes, and makes it easy to do so, leading Reed to conclude that hitting AOL’s scale requirements “would have been much harder with other technology.” Tagged with: AOL, Advertising, case study, use cases, flexibility, dynamic schema, high performance, scalability

March 26, 2013

Pearson / OpenClass Uses MongoDB for Social Learning Platform

We recently spoke with Brian Carpio of Pearson about OpenClass , a new project from Pearson with deep Google integration. What is OpenClass? OpenClass is a dynamic, scalable, fully cloud-based learning environment that goes beyond the LMS. OpenClass stimulates social learning and the exchange of content, coursework, and ideas â€â€ù all from one integrated platform. OpenClass has all the LMS functionality needed to manage courses, but that's just the beginning. Why did you decide to adopt MongoDB for OpenClass? OpenClass leverages MongoDB as one of its primary databases because it offers serious scalability and improved productivity for our developers. With MongoDB, our developers can start working on applications immediately, rather than slogging through the upfront planning and DBA time that relational database systems require. Also, given that a big part of the OpenClass story will be how we integrate with both public and private cloud technologies, MongoDB support for scale-out, commodity hardware is a better fit than traditional scale-up relational database systems that generally must run on big iron hardware. Can you tell us about how you’ve deployed MongoDB? Currently we deploy MongoDB in our world-class datacenters and in Amazon's EC2 cloud environment with future plans to go to a private cloud technologies such as OpenStack. We leverage both Puppet and Fabric for deployment automation and rolling upgrades. We also leverage Zabbix and the mikoomi plugin for monitoring our MongoDB production servers. Currently each OpenClass feature / application leverages its own MongoDB replica set, and we expect to need MongoDB’s sharding features given the expected growth trajectory for OpenClass. What recommendations would you give to other operations teams deploying MongoDB for the first time? Automate everything! Also, work closely with your development teams as they begin to design an application that leverages MongoDB, which is good advice for any new application that will be rolled into production. I would also say to look at Zabbix as it has some amazing features related to monitoring MongoDB in a single replica set or in a sharded configuration that can help you easily identify bottlenecks and identify when it’s time to scale out your MongoDB deployment. Finally, I would suggest subscribing to the #mongodb irc channel, as well as the MongoDB Google Group , and don't be afraid to ask questions. I personally ask a lot of questions in the MongoDB Google Group and receive great answers not only from 10gen CTO Eliot Horowitz , although he does seem to answer a lot of my questions, but from a many other 10gen folks. What is in store for the future with MongoDB at Pearson? Our MongoDB footprint is only going to continue to grow. More and more development teams are playing with MongoDB as the foundation of their new application or OpenClass feature. We are working on migrating functionality out of both Oracle and Microsoft SQL Server to MongoDB where it makes sense to relieve the current stress on those incumbent database technologies. Thanks to Brian for telling us about OpenClass! Brian also blogs at — be sure to check out his posts on MongoDB here and here and here and here and here . Tagged with: case study, Pearson, OpenClass, scalability, flexibility, ease of use

February 28, 2013

Guest post: runs Turkey's Internet on MongoDB About SPP42

This is a guest post by Emrah Ozcelebi, CEO of SPP42 , a leading NoSQL consultancy in Turkey. Nokta , one of the largest Internet companies in Turkey, knows what it means to operate at scale. The Internet leader reaches over 84% of all Turkish Internet users, and its video platform, , delivers more than 2.7 million videos with over 2 billion page views and significant video views. As a Facebook Timeline launch partner, Nokta’s also enables significant video sharing on Facebook. Finally, Nokta also operates Turkey’s leading photo sharing site, Foto Kritik , as well as a blogging site, Blogcu , that welcomes more than 13 million unique monthly users. At the heart of all this data is MongoDB. But Nokta got off to a rough start with MongoDB, due primarily to poor configuration and an inappropriate use case. Working together, 10gen and SPP42 were able to turn things around. First we got in touch with Nokta’s game department. Its Facebook implemantation of a local board game, OkeyHane was built on PHP, Java and Flash technologies with an open-source RDBMS as the database back-end. We were able to replace this relational database with MongoDB and significantly improve performance. It didn’t take long for Nokta’s software developers to realize that the flexibility of BSON gives extreme agility to the development team. Soon the MongoDB replicaset behind OkeyHane proved itself to be highly stable in production, in addition to being very easy to maintain and administer a MongoDB replicaset compared to other RDBMS solutions. After MongoDB proved itself stable in the midst of a difficult “war zone,” Nokta decided to extend its adoption by also using MongoDB in its flagship product, Nokta also elected to employ MongoDB in its homegrown advertisement platform, which feeds all its sites and delivers ads to 15,000 to 40,000 concurrent users. In order to meet the real-time requirements of the advertisement system, we helped to stabilize MongoDB installations. The middleware is built with the Akka concurrent programming framework with Scala language, with Spray being used as Rest API layer. We worked with great guys from like Erdem Agaoglu (@agaoglu) and Hakan Kocakulak who are also highly skilled in Hadoop and HBase. After the proven success of battle-hardened MongoDB installations in the ad-serving application, the developers became more eager to use MongoDB for storing metadata about users and videos. Nokta is now planning to replace all of its open-source RDBMS implementations with MongoDB. Of course, at that level of traffic, there is no single silver bullet to solve all problems. The skilled development team is aware of that and willing to try new technologies. SPP42 and Nokta are working together to deliver better services to Nokta’s users by combining different NoSQL solutions such as Hadoop and Neo4J. With help from 10Gen, we are able to offer better, integrated solutions to meet Nokta’s demands. There is a great wind filling NoSQL’s sails in Turkey. Although adoption is still at a very early stage, we are finding great success (and plenty of MongoDB interest) as a 10gen partner in Turkey. Companies like Nokta are able to achieve serious scale and improved developer productivity with MongoDB, helped by working with an experienced local partner like SPP42. SPP42 is a Turkey-based consulting and training company specializing in decision support systems and business intelligence. Since its founding, SPP42 has delivered top-level open source consultancy and training services - mainly Java, Pentaho, Jasper and Python solutions over OpenStack, OpenShift and MongoDB and other NoSQL solutions. SPP42’s services include end-to-end integration solutions, from development and architecture to implementation. SPP42 works with Turkey’s leading companies and helps them stay on the bleeding edge of technological innovation. We help them plan the migration from its existing technologies to newer ones so that our customers are always competitive globally. Tagged with: guest post, scalability, Scala, RDBMS, Turkey, SPP42, partner, ease of use, developer productivity

February 13, 2013