Justin Levandoski + Dharma Shukla (Microsoft)
Azure DocumentDB is Microsoft’s multi-tenant distributed database service for managing JSON documents at Internet scale. DocumentDB is now generally available to Azure developers. Built from the ground up as a multi-tenant service, DocumentDB is designed to operate within extremely frugal resource budgets while providing predictable performance and robust resource isolation to its tenants. DocumentDB indexing enables automatic indexing of documents without requiring a schema or secondary indices. Uniquely, DocumentDB provides real-time consistent queries in the face of very high rates of document updates. This talk provides an overview of the DocumentDB system along with details of the indexing subsystem, including document representation, query language support, the index implementation methods based on lock-free and log-structured technology, as well as early production experiences.
Justin Levandoski is a researcher in the database group at Microsoft Research. He is interested in a broad range of topics dealing with large-scale data management systems. Current interests include main-memory databases, database support for new hardware platforms, document-oriented databases, transaction processing, and cloud computing. His research has been commercialized in a number of Microsoft products, including the SQL Server Hekaton main-memory database, Azure DocumentDB, and Bing.
Dharma Shukla is a founder of the DocumentDB project and currently leads the DocumentDB engineering team at Microsoft. Dharma joined Microsoft in 1997 and has contributed to a variety of Microsoft products and services in the areas of cloud infrastructure, multi-tenancy, replication, database management, messaging, and workflow management systems.
More Info: http://www.pdl.cmu.edu/SDI/2015/043015.html