Speaker: Andrea Martorana Tusa
SQL Server 2017 introduced the extension for graph databases; and with SQL Server 2019, some key feature has been added. As there are millions of SQL Server users worldwide, this release broadens enormously the audience of potential users. Graph databases are born to address the need of handling complex relationships in an increasingly interconnected world. They make it easier to write queries in certain scenarios. Typical use is for querying hierarchical data, leveraging many-to-many relationships or analyzing network interconnected data. But, what to expect exactly from a graph database? How to query it? Is it worth investing time to learn it? Is SQL Server fully featured compared to other commercial products? In this session we answer these and other questions. We start illustrating the concepts behind the model; how relationships are handled and what are the common patterns and issues for a graph. What are the data connections a graph can easily sketch up. Then we compare the semantic model with SQL Server to discover how to apply it to real world. We analyze some case study: pattern matching, path finding, aggregation, ranking … For each of them we show how to use standard T-SQL and how to rewrite the query using graph objects. What is the benefit of reformulate our queries in terms of clearness and performances, what is already available and which features are still missing in order to consider SQL Server a valuable player in the databases arena.