Скачать или смотреть Graph Data Models and Query Patterns using

Graphs (as in nodes and edges) are well known data structures which make representing complex real-world scenarios much easier. Using node and edge tables, MATCH predicates, and regular T-SQL skills, developers can implement powerful query patterns for both OLTP and some analytical scenarios, all operating on the same efficient and secure data store that #AzureSQL provides. In this session we will examine some examples representing typical customer scenarios, and queries ranging from simple filters to complex analytical graph algorithms.

Arvind Shyamsundar is part of the Product Management team for Microsoft Azure SQL Database. His areas of focus include Azure SQL Hyperscale, SQL Graph, and DevOps. Previously Arvind was part of the AzureCAT / DataCAT / SQLCAT group at Microsoft, and prior to that was a Principal PFE with Microsoft Services. He is also the author of the popular SQLCallStackResolver tool and has published many other interesting samples at https://github.com/arvindshmicrosoft

Shreya Verma is a Program Manager on the SQL Server team. She has over 15 years of experience in the database industry, working on both SQL and NoSQL products. As a Program Manager in the SQL Server team, Shreya focusses on graph data processing capabilities and database backups. Prior to this, Shreya has worked on Amazon DynamoDB and ANTs Data Server products.