Apache Spark and MongoDB – Turning Analytics into Real-Time Action
Apache Spark is one of the fastest growing big data projects in the history of the Apache Software Foundation. With its memory-oriented architecture, flexible processing libraries and ease-of-use, Spark has emerged as a leading distributed computing framework for real-time analytics.
Unlocking Operational Intelligence from the Data Lake
Hadoop-based data lakes are enabling organizations to efficiently capture unprecedented volumes of data generated by new classes of highly connected applications. But without being able to expose that data to operational applications, users are struggling to maximize returns on their Hadoop investments. Read this white paper to learn how to create an operational data lake.
Big Data: Examples and Guidelines for the Enterprise Decision Maker
Despite the hype, big data is more than just a buzzword. Big data is enabling organizations to create new products, to outpace their competitors and to save tens of millions of dollars. In this paper, we begin with a description of big data and the data management landscape. Next, we describe examples of customers innovating with big data using MongoDB, the leading non-relational database, which has been a catalyst of the big data movement. Finally, given the nascent state of the market, we provide guidance to organizations selecting technologies for their big data projects.
MongoDB: Bringing Online Big Data to BI & Analytics
Big data is an essential extension of BI & analytics platforms, presenting new sources of operational insight & discovery. However, the rate of data ingestion coupled with its complexity & volume are beyond the constraints of many traditional databases used in today's BI systems. With its rich document model, powerful analytical capabilities and integration with leading BI and analytics tools, learn how MongoDB provides a foundation to integrate online big data with existing BI and analytics platforms.