Resources

MongoDB 3.0: What's New

MongoDB 3.0 is the newest and most significant release of the world’s fastest growing database. MongoDB 3.0 radically expands the use cases for MongoDB, allowing you to use it for the vast majority of all new applications. By improving performance by 7x - 10x, reducing storage needs by up to 80%, and lowering operations overhead by up to 95%, MongoDB 3.0 also dramatically improves your ability to deliver apps to market faster and more efficiently than ever before.

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Webinar: Backing Up Data with MMS

This presentation covers how MMS can be used to backup and restore your data from MongoDB. This presentation also covers backing up both replica sets and sharded environments, and discusses how to do point-in-time restores and restoring from snapshots.

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Webinar: Modern Databases for Modern Application Architectures: The Next Wave of Design, Development and Delivery

Application architecture has drastically shifted over the last decade and even more significantly in the last five. Clusters of confluence have brought about new approaches to design, development and delivery and in turn new technologies have risen to support the change. How do you know which addresses the real needs of the business? What impacts does this have to application, platform and next-generation development? What does an application look like now? In this webinar, we will review: Five trends that precipitated the change in application design; Four major outcomes; Need for an alternative approach to data; Four gaps these changes have created in people, process and technology.

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Positive Disruption in the Enterprise: How Infusion Approaches New Technology Adoption with their Clients

This presentation focuses on Infusion's strategic approach to organizational transformation in partnership with MongoDB. When our first customer asked us for our experience with MongoDB two years ago, we responded accidentally something along the lines of "We've heard great things about MangoDB." We knew of the product but our experience was limited. Our story centers around the path forward from there and what we have learned in this journey from experimentation to deployment. We will leverage real customer examples to highlight the journey forward and our methodology.

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Webinar: Big Data: Guidelines and Considerations for the Enterprise Decision Maker

The Big Data space is not entirely new, yet organizations still face difficulty in understanding how it leverages the rest of their business and technology footprint, never mind actually implementing it. Equally important is understanding when you should be asking what kinds of questions and how to act on the answers. This presentation outlines important concepts that will help you more clearly delineate activities and business value that are produced from different parts of the technology footprint. More specifically, we cover an approach to using MongoDB together with Hadoop to direct the "best" content to users by managing real-time user profiles, combining data, process, and technology to connect short term and long term analysis.

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Webinar: Understanding MMS - Getting Started with MMS

MongoDB Management Service (MMS) is the application for managing MongoDB, created by the engineers who develop MongoDB. This session of our Understanding MMS Series introduces MMS, helps you to understand at a high level what it does, add users and permissions, and shows how to get started with downloading and installing the agents.

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Webinar: MongoDB for Time Series Data: Sharding

In the third part of our MongoDB for Time Series Data presentation series, we’ll need to set MongoDB up to perform under heavy loads. MongoDB offers sharding capabilities so we can horizontally scale our application and ensure consistent performance. In this third part of our webinar series, Jake Angerman will go through sharding options in our Time Series application. You will walk away deeper understanding of how to configure your sharding setup, choose a shard key and leverage this feature for optimal scale.

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Industrial Internet and Intelligent Machines with MongoDB

Smart Factories with M2M communications is the main goal of the fourth industrial revolution. The “Industrial Internet” as it is called by GE or the “Industry 4.0” project by the German government revolve around Big Data and Analytics. The machine building industry faces challenges in emerging markets such as high energy costs and a shortage of skilled staff, which drive the need for highly-optimized and self-optimizing machines. We will use the example of a world leader in this sector to describe how we built a system for real-time analytics of machine sensor data, using MongoDB as the heart of an easily scalable and decentralized storage system for operational data. Customers of Brückner Maschinenbau GmbH use the system to gather data from their production lines, monitor the quality of their products and optimize their production-processes with prediction analyses and deep production insights through machine learning algorithms.

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Webinar: 3 Ways Modern Databases Drive Revenue

In this webinar session, Matt Asay, VP of Marketing at MongoDB, discusses the evolution of the modern database and the advantages of modern databases today.

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Webinar: MongoDB for Time Series Data: Analyzing Time Series Data Using the Aggregation Framework and Hadoop

The United States will be deploying 16,000 traffic speed monitoring sensors - 1 on every mile of US interstate in urban centers. These sensors update the speed, weather, and pavement conditions once per minute. MongoDB will collect and aggregate live sensor data feeds from roadways around the country, support real-time queries from cars on traffic conditions on their route as well as be the platform for real-time dashboards displaying traffic conditions and more complex analytical queries used to identify traffic trends. In this second webinar of our webinar series, we’ll implement a few different data aggregation techniques to query and dashboard the metrics gathered from the US interstate.

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Data Integration and Advanced Analytics for MongoDB: Blend, Enrich and Analyze Disparate Data in a Single MongoDB View

Creating a single, 360° analytical view of an entity such as a customer, employee or financial investment can have a big impact on your business, but blending data from proprietary and open, unstructured data sources can be a development challenge. Pentaho can accelerate your MongoDB development efforts by making it easy to enrich data with predictive scoring and blend data from disparate sources into a single MongoDB view. In this session we will discuss the single view use case and perform a live demonstration of blending real-time Twitter feeds with NASDAQ stock quotes into a single MongoDB view for understanding the impact of Twitter sentiment on stock valuations.

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Service-Oriented Clusters at Foursquare

Foursquare has been a long time user of MongoDB and currently uses it to serve almost all hot data. We've always run multiple sharded clusters to handle different types of data, but recently we started to split out collections into clusters that align with specialized services. I'm going to talk about the motivation behind isolating MongoDB clusters for specific internal applications and the tools we've used to make that possible without any downtime.

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