use cases

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

Guest post: Using MongoDB to build government warning systems About VX Company

This is a guest post by Bas van Oudenaarde, Technical Manager, VX Company One of the primary roles of government is to care for the safety of its citizens. Depending on the country, there are different public alert and warning systems to notify civilians of general or local dangers. Historically, such systems have tended to be 'top-down' or hierarchical, but today bottom-up approaches are preferred as news tends to travel much faster through social media like Twitter or Facebook than outmoded means. VX Company builds such public alert and warning systems for governments, and has been evaluating how best to re-engineer its systems using MongoDB. Challenge Recently VX Company developed a novel approach using MongoDB and its built-in geospatial, sharding, replication, and other features. In this prototype, which we defined as an interim project for students, we explored a ‘bottom-up’ approach using a mobile app interfacing with a distributed servers layer with MongoDB nodes. The students got just six weeks to implement these new concepts with MongoDB: design, build, and test. By constraining the delivery deadline, both the students and MongoDB were put to the test. In this new application, a civilian could sent out a message to their neighborhood to get help in case of an emergency situation. For purposes of this system, ...neighborhood“ (or ...cell“ in our terminology) is determined by the type of emergency, so in the case of a robbery the neighborhood or cell might be 10 kilometers around the hotspot. Different emergency problems result in different sizes of cells. In each cell the government can respond to incidents, for example, by sending a fire truck or ambulance, or local neighbors can help or give more information, as appropriate. Alternatively, the government organization could broadcast warning of a problem to a cell. Whether at home or roaming, citizens can both send and receive notice of emergencies. Architecture In order to implement the system we used MongoDB together with the following components: Google API to communicate with the location server On the application level, a JSON-based REST layer that is implemented with Java 7 A push server Load balancer (optional) Any mobile device (BYOD: HTML5/JavaScript-based) Using this architecture provides a lightweight, highly scalable (cloud) solution. Why MongoDB? MongoDB is a great fit for such a distributed system. MongoDB supports location-based queries, provides location positions (longitude, latitude) with a radius and allows for easy retrieval of all persisted messages in this range. Other useful MongoDB features are sharding, replication, and JSON data interchange. Instead of storing all information centrally, sharding data lets organizations store data where it makes sense, and quickly respond to local content. In case of citizen roaming we actually have to deal with two locations, e.g., home and visit location. In addition, reliability of the data is critical in such a system. MongoDB ensures the reliability of data through support for out-of-the-box replication. Finally, MongoDB uses JSON for data exchange and hence fits naturally with mobile computing. Another important point is that MongoDB works well in cloud environments like Amazon Web Services, so that if the application proves successful we can easily and cost effectively scale it out. Initial Results? As mentioned previously, the students had just six weeks to design, build, and test their MongoDB-based emergency alert and response solution. Despite the tight time constraints, the students successfully completed this project in time and with the requisite functionality. For the project the SCRUM approach was used. In total we had three code sprints, with each sprint lasting two weeks.The first sprint was used to set up the key elements of the architecture and sketch the model. For the following two sprints, after each sprint the students delivered a working solution to the client to determine whether the product was ready or still needed adjustments. After six weeks the product was complete, consisting of a running model (which runs the predefined test cases), documentation, API information, installation manual and test setup. These promising results confirmed for us that MongoDB could significantly expand new possibilities, while simultaneously making our lives easier. A lot of interesting mobility features are built into MongoDB and we plan to explore more concepts and build them into future releases of our civilians watch application. In particular, we would like to integrate common social media like Twitter and Facebook, both to generate interest and adoption of the application, but also to improve its utility. VX Company, founded in 1988 and based in The Netherlands, is an IT service provider active in consultancy, projects and secondment in the field of Microsoft, Java, Oracle, OpenVMS, Unix and Linux. Almost 300 IT professionals work on the analysis, design, development, integration, testing and management of applications and computing infrastructures for many customers. Moreover VX Company is a specialist in the field of managed services and project management. The company is characterized by a culture in which the employee is the core of success. That's why Computable named VX Company ...Best ICT secondment company of the year,“ ...Best ICT employer,“ and one of ...the most powerful IT service providers in the Netherlands.“ Learn more at . Tagged with: government, guest post, VX Company, public alert and warning system, geospatial indexing, use cases, case study

February 4, 2013

Get Ready for MongoDC

MongoDC is happening on June 26 at the Wooly Mammoth Theatre in Washington DC. At MongoDC many attendees are just learning about or evaluating MongoDB to see if it is the right fit for their use case, while others are in development or in production and are looking for a little more depth. A lot of your are also interested in best practices to optimize your use of MongoDB. To help you plan your day, here’s a curated list of talks for you to attend based on what you’d like to get out of MongoDB. Optimizing MongoDB Schema Design by Example with Robert Stam, 10gen Data Safety with Mathias Stearn, 10gen How and When to Scale MongoDB with Sharding, Tyler Brock Deployment Preparedness with Dan Crosta, 10gen Operations Best Practices with Michael Fielder, 10gen Indexing and Query Optimization with Robert Stam, 10gen Learning About or Evaluating MongoDB for a Future Project Schema Design by Example with Robert Stam, 10gen An Overview of Replication with Edouard Servan-Schreiber Data Safety with Mathias Stearn, 10gen Deploying MongoDB with Chef with Nathen Harvey, CustomInk Whiteboard Open Q&A with Michael Fiedler — to answer all the questions you came up with along the way MongoDB on Amazon EC2 with Michael Fiedler, 10gen Developing or In Production with MongoDB Journaling and the Storage Engine with Mathias Sterne, 10gen Operationalizing MongoDB at AOL with Michael DelNegro, AOL Advanced Replication with Edouard Servan-Schreiber, 10gen Big Data Aggregates with MongoDB and Hadoop with Jason Booth, six3 How IKANOW Uses MongoDB to Help Organizations Solve Really Big Problems with Craig Vitter, IKANOW Whiteboard Q&A: Hadoop with Tyler Brock, 10gen The New Aggregation Framework with Tyler Brock, 10gen There’s also a number of talks that don’t fit into these two categories, but help to illuminate interesting MongoDB use cases. Exploring MongoDB Use Cases Panel: Big Data and MongoDB in the Federal Government Practical Use of MongoDB for Node.js with Jonathan Altman, Software Engineer Mongo or Die: How MongoDB Powers “Doodle or Die” with Aaron Silverman Taming Social Media with MongoDB Mobilizing MongoDB! Developing iPhone and Android Apps in the Cloud with Marek Jelen, Red Hat Why We Chose MongoDB to Put Big Data on the Map, Nicholas Knize, Thermopylae Sciences and Technology This should help you work through the MongoDC schedule. If you have any questions about sessions, feel free to ask 10gen staff at MongoDC! And if you haven&88217;t registered yet, now is the best time to do so! Tagged with: mongodc, use cases, database, big data, data storage, computers, it, technology, MongoDB, Mongo, NoSQL, Polyglot persistence, 10gen

June 25, 2012