MongoDB on Red Hat Enterprise Linux

MongoDB on Red Hat Enterprise Linux

On demand

Red Hat® Enterprise Linux® powers mission-critical applications for thousands of enterprises, delivering performance, reliability, scalability, and security.

MongoDB is an open source, document-oriented database designed with both scalability and developer agility in mind. Instead of storing your data in tables and rows as you would with a relational database, in MongoDB you store JSON-like documents with dynamic schemas. The goal of MongoDB is to bridge the gap between key-value stores (which are fast and scalable) and relational databases (which have rich functionality).

In this webinar, we'll walk through some of the steps necessary to deploy MongoDB on Red Hat Enterprise Linux 6.2 and take advantage of several features of the underlying system. Using multiple example deployment scenarios, we'll review issues like configuring storage, server security, and system monitoring. These steps can serve as a basis for deploying MongoDB in your own Red Hat Enterprise Linux environment.


Sanjay Rao, Principal software engineer, Red Hat
Sanjay Rao is a principal performance engineer working on the performance engineering team at Red Hat for a little more than 5 years. The performance engineering team works for the chief technology officer's office. The focus of the team is to evaluate performance of the Red Hat platform by itself and with various partner applications. Most of the testing done in the performance lab is geared towards enterprise deployment. Prior to working for Red Hat, Sanjay worked in a performance engineering organization at Hewlett Packard (HP) for 8 years, and 10 years before that as a production systems and database administrator for large financial institutions.

Sandeep Parikh, senior technical product manager, 10gen

Before joining 10gen, Sandeep wrote code for Ravel where he developed a large-scale graph processing framework on top of Hadoop. His background is in software engineering and he has developed systems for social network analysis, natural language sentiment, and text similarity. He lives in Austin, TX, where he helps run the Austin NoSQL meetup group and sometimes rides his bike.



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