MongoDB Connector for Hadoop Now Certified with Top 3 Hadoop Vendors
We’re excited to announce that our MongoDB Connector for Hadoop has just been certified on MapR’s latest distribution, 4.0.1 . The connector, which allows customers to use MongoDB as an input source and/or output destination for Hadoop deployments, is now certified on distributions from all of the leading vendors in the space, including MapR , Hortonworks , and Cloudera . As an operational database for use cases such as Single View , Internet of Things , Real-Time Analytics , and more , MongoDB is the perfect technology complement to Hadoop. With the connector, live data from MongoDB can be brought into Hadoop, enriched through analytics (often with data from other sources), and then passed back into MongoDB to better serve user-facing applications. Orbitz, the travel booking company, uses MongoDB and Hadoop together to deliver real-time pricing and compete for travel shoppers. MongoDB serves as the data collector while Hadoop is used to store and analyze the data. The City of Chicago built a futuristic predictive analytics platform using MongoDB and Hadoop Their WindyGrid system allows officials to access a real-time view into crime, public health and other citizen issues. Data analysis allows the city to predict disease outbreaks and decide in real-time where to place first responders. Other Common Use Cases That Leverage MongoDB + Hadoop Ecommerce MongoDB can be used to... Hadoop can be used to… Store products, inventory, customer profiles, clickstream data Run real-time recommendations Session management Detect Fraud Store complete transaction history, and clickstream history Build recommendation model and fraud detection models Insurance MongoDB can be used to... Hadoop can be used to… Store insurance policies, customer web data, call center data, demographic data Real-time churn detection Conduct customer action analysis Create churn prediction algorithms Learn more about how Hadoop and MongoDB can work together [here](http://www.mongodb.com/hadoop-and-mongodb). What’s next? Get started by checking out the documentation on the MongoDB Connector for Hadoop or learn more at one of our upcoming MongoDB Days: MongoDB London , 11/6; MongoDB Munich , 11/12; MongoDB Paris , 11/18; MongoDB Beijing , 11/22; and MongoDB SF , 12/3.
Mike Olson On The Past And Future Of Data
Data today is very big, but it's not because any particular individual or company is creating lots and lots of data. Instead, we live in a new machine age, with a vast proliferation of machines emitting data in volumes and variety the world has never seen. As such, no single company will be big enough to tackle Big Data alone, declared Cloudera co-founder and chief strategy officer Mike Olson in his MongoDB World keynote this week in New York City. There Is No Big Bang Big Data isn't about Big Companies or other single sources of data. U.S. homes now hold over 500 million Internet-connected devices at an average of 5.7 per household, according to NPD. By 2017 each person will have 5 Internet-connected devices, with each one contributing to a torrent of data. In the past, Olson indicated, we built big, centralized databases, which were good at a managing data created at human scale. They were awesome for their generation. But they’re simply not good enough for the world of machine-generated data, i.e., the world we live in now. These relational databases were designed for a world that didn’t need to account for the incredible variety and petabyte-scale of machine-generated data. Google introduced us into a new, small flexible incremental architecture, which gave us a new way to think about hardware and software and, really, a new way to think about data. Google also gave us a new way of thinking about how to capture, store and analyzing data. That "new way" is the cloud. As he stressed, data will tend to remain where it was generated. Given that the vast majority of new data is created in or for the cloud, modern databases must also live in the cloud. One Database To Rule Them All? While it's tempting to think history will repeat itself and one company will dominate Big Data, such a zero sum, one winner-takes-all outcome is unlikely. The reason? The power of a data hub or platform derives from its ability to collect data from small, disparate systems, loosely coupled, rather than from owning the Big Data "stack." Hence, while Olson at one time thought Cloudera, MongoDB and Teradata would fiercely compete to manage the same data, the reality is that the three companies now work closely together to take care of data at all points in the data lifecycle. Big Data is not zero sum. It's not created by any single entity, and it can't be controlled by any single entity. A community is required. As both Olson and MongoDB CEO Max Schireson insisted in their respective keynotes, that community is comprised of Cloudera and MongoDB working together to solve customers' biggest Big Data problems. To see all MongoDB World presentations, visit the [MongoDB World Presentations](https://www.mongodb.com/mongodb-world/presentations) page.