Breaking Barriers: MongoDB Design Patterns
MongoDB does a fantastic job of storing humongous data sets, but what does our application need to take into consideration in order to cope, and how should the data be structured? This tutorial is an intermediate / advanced session focusing on development for MongoDB considering several important design patterns and techniques for robust code implementation and database design. The discussion will cover the following areas: - Indexing strategy - Data modeling: To reference or to embed? - Ranking / Fast accounting in MongoDB - Atomic updates and the optimistic locking pattern - Defensive programming - Read / Write concern - Sharding considerations
Big Data Architect, Pythian
Christos is a principal architect at Pythian creating and delivering Big Data platforms for some of the world's top tech organizations. Having more than 15 years of experience in designing and implementing software, he has a strong interest in building scalable, high throughput systems.
Senior Technical Operations Architect, Percona
Nik Vyzas is a senior technical operations architect with 12+ years experience in production support and enterprise software development for large scale distributed environments using a variety of open-source technologies such as RHEL, Debian, Percona Server, XtraDB Cluster, MongoDB, Puppet, Ansible, Java and Python. Over the years he has also mastered the dark art of turning caffeine into new software and bug fixes... his hoodoo mantra is "computers just do what you tell them to do".