Resources

Two Years of MongoDB at Sailthru

Sailthru is a behavioral communication and analytics platform focusing on email, onsite, and mobile personalization. Sailthru stores terabytes of data for hundreds of millions of end users and billions of messages, all in MongoDB. Since we presented last year, we've had 10x growth and experienced lots of challenges scaling on AWS. We've learned lots of lessons about building and designing for MongoDB at scale, and we'll share them.

NYT + MongoDB in Production

This is a follow up talk to Jake Porway's talk at MongoNYC 2011 where he presented Project Cascade as one of R&D Labs Projects backed by MongoDB. Since then Project Cascade has moved to a scalable production level system. The talk will cover challenges and lessons learnt in moving MongoDB from a research project to a production environment.

How MongoDB is Helping Shape the Future of the Music Industry

MongoDB is helping Next Big Sound change how the music industry uses big data. By marrying social media data with traditional sales data, Next Big Sound creates a central platform for all of the music industries needs with MongoDB working hard behind the scenes. This use case analysis will hit key points such as cluster architecture, document schema, some growing pains, and how Next Big Sound uses MongoDB to store rich event data as well as index hundreds of thousands of artists by their network distribution and geolocation.

5ivePoints: 130 Million Voters and Counting

At 5ivePoints, we have a MongoDB database with 85+million US voters, every one of them geocoded. Our application allows supporters of political campaigns across the country to pull up nearby voters on their mobile phone to canvas. Moreover, campaigns can create custom filters using any combination of voter attributes, and we provide data-driven filters that update in near real-time based on campaign results. But with a collection of this size, each index is on the order of GBs, and un-indexed queries aren't feasible. I'll discuss how we are able to support flexible user queries - integrating both geo-spatial and other attributes - with only 4 indexes, minimizing page faults caused by pulling rarely-used indexes into memory.

MongoDB per TIM - 15 DICEMBRE

Omnichannel, Personalization and more for Retail

The convergence of retail to an omnichannel experience drives new requirements to the data platform and the handling of data. While retailers have used analytics in their day to day operations for a long time, there is a shift towards reactions measured in seconds or milliseconds – converging the online and store experiences. Retailers must adapt and be able to analyse current and older data in real-time on a converged data platform, regardless of the data sources. In this on-demand webinar we will walk you through the fundamental technologies for the various real-time use cases and their criticality for success in the retail industry. We will be covering: Personalisation and Next Best Offers : offering real-time personalisation when consumers shop online or in-store. Recognise your customer when they return to your site or app and match their preferences and history to products that have context. Supply Chain Management : real-time analytics is disrupting the supply chain sector, enabling more complex supplier networks. Huge volumes of data are analyzed to report warehouse inventory and POS inventory, as well as being used to predict production and shipment needs. This real-time efficiency verifies retailers have the right products and volumes at the right time – if not, offer relevant product substitutions in real-time. Fraud Detection : classifying a card transaction as fraud is based on complex logic of 100+ queries, all working coherently to identify potential fraud patterns. The moment a card is swiped, the database must determine whether to decline the transaction within milliseconds.

What Is Hadoop?

Powerful business insights from Hadoop and MongoDB Hadoop is an open source software that stores and processes large volumes of data for analytical and batch operation purposes. Like many other modern, open source technologies, Hadoop makes use cluster of commodity servers and commodity storage. Using MongoDB together with Hadoop, you can create powerful applications that perform sophisticated analyses with your data and uncover new opportunities for business growth. MongoDB is the database behind real-time operational applications. Hadoop takes data from MongoDB as well as from other operational systems to perform complex analytics and drive machine learning. Together, these two technologies complement each other to result in greater business intelligence. Many users of MongoDB rely on this integration, through the Hadoop Connector, to develop innovative applications that harness the power of Big Data. The City of Chicago, for example, uses MongoDB along with Hadoop to power its innovative application called the WindyGrid. The city built WindyGrid, a predictive crime prevention tool, to analyze data from over 30 different city agencies and predict future outcomes on crime, public health and other key issues affecting citizens. As a result, the City is able to do amazing things like predict disease outbreaks and decide in real-time where to deploy first responders. The City of Chicago is not the only entity to benefit from the power of using Hadoop and MongoDB together. Enterprises as diverse as eBay, Orbitz, FourSquare and Pearson also benefit from this integration to drive new insights to grow their business. Combine these two forces and see what it can do for your business. Watch the video MongoDB & Hadoop - Driving Business Insights.

Top NoSQL Databases

The advantages of NoSQL databases over traditional relational databases are clear. NoSQL databases overcome the limitations of relational database technology when it comes to meeting the requirements of modern day, Big Data applications. This new class of technology offers greater scalability, superior performance, and data models that are better suited to the typically unstructured data that predominates today. But choosing which NoSQL database to go with to best satisfy your requirements isn’t easy. There are many NoSQL technologies, all with their own benefits and features, and they share little in common except for the fact that they are not a relational database. Starting with the top NoSQL databases, you will find that MongoDB is a clear leader in a crowded field of options. In fact, MongoDB is consistently ranked as the most popular NoSQL database according to the DB-Engines monthly rankings. And in recent months, Gartner has named MongoDB as a leader in the operational database management space. As the most popular database with over 40 million downloads and counting, MongoDB has a robust developer community and over a 1,000 partners to help you get started on a deployment. Because of this momentum, enterprises of all sizes, from the latest startup to Fortune 100 companies, are opting for MongoDB as their NoSQL database standard. Popularity shouldn’t be the only criteria behind your decision to use MongoDB. There are several reasons why MongoDB could be right solution for your organization. To find out more, download our white paper on the important dimensions to consider when evaluating NoSQL technology.