MongoDB has been designed for versatility, but the techniques you might use to build, say, an analytics engine or a hierarchical data store might not be obvious. In this talk, we'll learn about MongoDB in practice by looking at four hypothetical application designs (based on real-world designs, of course). Topics to be covered include schema design, indexing, transactions (gasp!), trees, what's fast, and what's not. Sprinkled with tips, tricks, shoots, ladders, and trap doors, you're guaranteed to learn something new in this interdisciplinary talk.

MongoDB supports write-ahead journaling (by default) to facilitate fast crash recovery and consistency in database files after that crash. In this session, we'll give an overview of on-disk persistence with MongoDB, journaling, and discuss the internals of journaling and the storage engine.

Rangespan is building the biggest product catalogue in the world. If you can buy it, we want to sell it. Since our launch a year ago this month, MongoDB has been at the core of our architecture. I'll share our journey from one laptop to a high-availability architecture on AWS, how we benchmarked our MongoDB configurations, implemented a pub/sub system, integrated elasticsearch, and all the mistakes in between.

We will build an IRC server based on MongoDB. In this first session we will review how the server works and how to manage the necessary data. We will look in detail at how to build a Message Bus that is the backbone of our IRC server.

MongoDB supports a wide range of indexing options to enable fast querying of your data. In this talk we’ll cover how indexing works, the various indexing options, and cover use cases where each might be useful.

This talk is about the interest and adoption growth of a Research and Development company like Telefonica R&D. Going through the different phases that new technologies pass till they are accepted and adopt within the technological mindset of a company. I'll discuss those phases @Telefonica, the different steps that mongoDB is taking within the projects, the different problems that add to be dealt with towards the general consensus, the way project members start to see mongoDB, the corporate view towards this new technological solution and the way customers come along and start to trust on solutions that present mongoDB as part of the "package". Part of the talk is to give an insight of how 10gen has helped to develop a good understanding of the technological advantages, the training and support provided which leads to a better adoption of the product.

Graph databases store store data represented as nodes, edges, and properties. Semantic web and linked data developers use graph stores based around the W3C's Resource Description Framework (RDF) standard to manage and store data. Talis have a number of commercial applications based on the RDF standard that require a higher level of performance than is achievable with today's RDF-based graph databases. In this talk we will discuss how we turned to MongoDB to provide a high performance way to manage RDF data. We will introduce the thin library layer we use on top of MongoDB, showing how we gained an order of magnitude leap in performance, as well as reducing operational complexity in our stack. We'll demonstrate how we integrate the RDF, graph-centric view of the world with Mongo's document-centric approach. We'll discuss how we used materialised views, generated using map reduce, as well as how we used MongoDB to generate indexes for ElasticSearch on the fly. We'll show how our library presents a familiar interface for semantic web and linked developers so they don't need to substantially re-write their applications.

Now that we've built our app, we will look at how to deploy it in production. We will design and deploy a replica set to support a highly available backend for the server. We'll also show you how to monitor your server, both from the shell and using the MongoDB Monitoring Service (MMS). Additionally, we will try to break our cluster and show how the service stays running throughout failures as well as how to recover from catastrophic failures.

Overview of AOL's use of MongoDB within some of its advertising products, the kind of throughput we're getting from MongoDB and the lessons we've learned along the way.

Learn how to integrate MongoDB with Hadoop for large-scale distributed data processing. Using tools like MapReduce, Pig and Streaming you will learn how to do analytics and ETL on large datasets with the ability to load and save data against MongoDB. With Hadoop MapReduce, Java and Scala programmers will find a native solution for using MapReduce to process their data with MongoDB. Programmers of all kinds will find a new way to work with ETL using Pig to extract and analyze large datasets and persist the results to MongoDB. Python and Ruby Programmers can rejoice as well in a new way to write native Mongo MapReduce using the Hadoop Streaming interfaces.

Primer on horizontal scaling with MongoDB. Introduces the core concepts behind storing and querying large datasets in addition to presenting the architecture, mechanics, and configuration of a sharded cluster.

We will extend the IRC server to log the full chat history. This requires a scalable backend to store an infinitely growing volume of messages. We'll look at several ways of designing the message storage and the limitations and tradeoffs of each. We will then deploy our updated IRC server and upgrade from a replica set to a sharded cluster without any downtime.

We're working on a new aggregation framework for MongoDB that will introduce a new aggregation system that will make it a lot easier to do simple tasks like counting, averaging, and finding minima or maxima while grouping by keys in a collection. The new aggregation features are not a replacement for map-reduce, but will make it possible to do a number of things much more easily, without having to resort to the big hammer that is map-reduce. After introducing the syntax and usage patterns for the new aggregation system, we will give some demonstrations of aggregation using the new system.

Learn how you can add Activity Streams to your web applications with a few simple steps using Cloud Foundry, MongoDB and NodeJS. This hands-on session will walk you through the schema design, engine creation on Cloud Foundry and usage from any web client.

We will explore the various options for backups, go through the rich information available through the monitoring service (MMS), and observe the automated chunk split and automated chunk migration across shards. We will also provoke several failures in the cluster and see how to recover.

In this session we’ll talk through a series of examples to distill some of our best operational practices. The format of this talk is an interactive and fun adventure through some real-world cases that come from real systems and large deployments. This session will touch on backups, network availability, performance pitfalls, indexing/schema-design, log management, monitoring and alerting along with some good examples of diagnostic techniques with a goal of finding good solutions.

A look at how a small group of self-motivated developers went about introducing, first themselves, and then their organisation to MongoDB. What made them do it? How did they gain acceptance for a new storage system amongst their peers, administrators and development managers? What was it like to actually write code around MongoDB? Join us for the answers and get the inside story of an adoption mere months old.

This is an overview of the MongoDB architecture: the storage engine for bson and btrees, the query evaluator, the replication design, and the sharding design. The talk is more broad than deep, and it is intended to give an effective overview of the mongodb design decisions and implementation strategies.

This talk explores how to expand and contract a network deployment using multiple MongoDB environments with Ubuntu Server and Juju. In this talk we will show one way that related services can be deployed on multiple environments via Juju and still maintain connectivity between them. 

Government IT in the UK has traditionally been large, expensive and prone to failure. The needs of the user are rarely put first. In the UK 50% of the population have a facebook account, and government systems are looking increasingly cumbersome and out of touch to the next generation of digital citizen. Our mission at the Government Digital Service (GDS) is to change this, moving to a world where the digital channel is the default channel & user needs are a priority. We want to improve the experience of interacting with the government online. To do this we need simple & reliable tools and strong principles. In this talk Mat will illustrate how we are using MongoDB to support the development of a variety of government projects, and how it forms a key part of their toolset in the "Digital by Default" strategy of GDS.

Enterprise architects often use schema diagrams as if they are the diagrams of the entire system. This happens largely because schema diagram tools are the easiest solution available, and because they can automatically generate diagrams from a SQL database. This approach has some major drawbacks — the most serious being that applications directly access databases controlled by other applications and business groups. The talk will show why this is such a bad idea (basically, it can slow all development and improvement across the entire enterprise to a crawl), and give some ideas about how to fix the problem and introduce proper encapsulation back to enterprise computing. By moving away from modelling enterprise systems through relational schema diagrams and focusing on encapsulation of services, developers and architects are freed up to consider the most appropriate data storage product for their systems.

This presentation introduces OpenStreetMap and explains to the audience what sort of rich data set it has. I will also cover different APIs for using the map tiles as well as other APIs that form sister-projects to OSM, such as Nominatim (search), routing, and obtaining current-location information. For the data storage and querying aspects we will be looking at MongoDB.

In this talk we will explain the elements of a successful MongoDB deployment and focus on the where, how and why they fit into the development process.

Your operational data store problems have been solved with MongoDB. Now what do I do with all this JSON data? How will I report against it? How will I analyze it? How do I find those golden nuggets that I can monetize? And why are the Data Analysis and Data Scientists chasing me with an axe? In this talk we will look at the problem of data analytics from the developers and the analysts perspective and how the JSON data model breaks the existing tool chest used by these communities. First we will look at the in-built technologies of MongoDB, Map/Reduce and the Aggregation Framework. We will then see how Analytica's end user tools leverage these technology, which allow reporting and analysis of data directly against MongoDB through a powerful yet easy-to-use functional language (available as both a RESTful API and Excel plugin). You should walk away from this talk with practical strategics for knowing which tools to use when and for which problems.

This session introduces the basic components of high availability before going into a deep dive on MongoDB replication. We'll explore some of the advanced capabilities with MongoDB replication and best practices to ensure data durability and redundancy. We'll also look at various deployment scenarios and disaster recovery configurations.

Join us for a technical how-to session on how to develop multiplatform mobile applications using MongoDB backends for the cloud. Skip having to learn several different languages and jumpstart the development process using what you already know. We'll utilize jQuery mobile to create an awesome-looking mobile application targeting multiple mobile platforms and we'll deploy our app to the cloud right away. Finally we'll pull out our smartphones and bask in the awesomeness of our apps! Nothing complicated, nothing convoluted. Just straight ahead mobile development goodness with MongoDB.

There are many ways to build dashboards and reports with detailed aggregations. In this talk we will outline one way of using pre-aggregating as data is collected in order to provide real-time views. You may be familiar with options which include post data collection processing, like map/reduce or the new aggregation framework; we will investigate some of the downsides which we will need to be addressed when defining the use case for counters and pre-aggregation with MongoDB. Come learn how to build these types of reports and see how easy it can be.

Deploying into one data centre isn't enough. Networks fail, power outages happen and natural disasters can't be predicted. Ensure not only redundancy but localised speed by using multiple facilities...if only it were that easy. This talk is a look at the technical aspects of how to do multi-data centre deployments.

Sharding allows you to distribute load across multiple servers and keep your data balanced across those servers. This session will review MongoDB’s sharding support, including an architectural overview, design principles, and automation. Also will be presented varied scenarios of handling large amount of data, along with their best sharding strategies.

Have you always wanted to learn how to rewrite your own HTML5 retro game using Node.js and MongoDB with a multiplayer twist to it. Come play the game, learn how it was made and fork it.

Gain valuable insights on running MongoDB on Amazon EC2. EC2 provides a simple and flexible deployment model for your application and databases. However, you still need to manage, maintain, and monitor your system. So how do you do this with EC2? We'll explore these questions and more in this session.

MongoDB Oplogs are quite easy to manipulate, and are potentially very rewarding, especially when you need to perform live database migrations. This talk will give a short intro into replication and how oplogs work, then a deeper dive into what can be achieved by redirecting oplogs from one cluster to another. For example, you could force two distinct clusters to mirror each other, or just have one cluster copy another.