Back to Basics: Introduction to MongoDB
This is the first session in the Back to Basics webinar series. During this session we cover: A brief history of databases The Document Data Model The MongoDB Query Language (MQL) MongoDB's solutions Back to Basics Series Catch up on the rest of the series to learn the basics of MongoDB. Introduction to MongoDB Building Your First Application with MongoDB Atlas
MongoDB Atlas Best Practices
MongoDB Atlas is a database as a service from MongoDB, providing all of the features of the database, without the operational heavy lifting required for any new application. This guide describes the best practices to help you get the most out of the MongoDB Atlas service, including: schema design, capacity planning, security, and performance optimization.
Quantifying Business Advantage: The Value of Database Selection
Can the choice of database really dictate business outcomes? Consider: A leading insurance company delivering a new application in just 3 months, after struggling for 8 years with a legacy database. A global telecoms operators accelerating time to market by 4x and improving customer experience by 10x. A Tier 1 investment bank estimating savings of $40m. What do they all have in common? They all selected MongoDB to deliver applications never previously possible. Download the white paper to learn more
MongoDB Operations Best Practices
This document provides guidance on best practices for deploying and managing MongoDB clusters. It assumes familiarity with the architecture of MongoDB and a basic understanding of concepts related to enterprise software deployment. Because MongoDB is designed to be simple to administer and to deploy, most operations professionals find they can become competent with MongoDB in a short period of time and with minimal training.
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.