Greg McMurray presented on SQL Server Graph Database at a user group meeting, explaining the structure of graph databases, including nodes and edges that represent entities and their relationships. He discussed the capabilities and limitations of graph databases, showcased examples using Cypher Query Language, and highlighted new features in SQL Server 2019. McMurray encouraged attendees to explore graph databases and share their experiences with him.

1. Introduction to
SQL Server Graph DB
Salt Lake City SQL Server User Group
Greg McMurray – November 2018

2. GREG MCMURRAY
• Experience in Aerospace, Branding & Marketing,
Energy, Healthcare, Software
• Currently Senior Software Engineer at WECC
• Co-Founder of Aritus Computer Services, L.L.C.
• President of SharePoint / Office 365
and Dynamics 365 User Groups
• Find me online:
- @goyuix
- https://www.linkedin.com/in/goyuix
- https://stackoverflow.com/cv/goyuix
( top 2% of users )

3. WECC
• OUR MISSION:
“To effectively and efficiently reduce risks to the reliability and security of
the Western Interconnection’s Bulk Power System”
• Approved Regional Entity by Federal Energy Regulatory Commission
• Creation, Monitoring, and Enforcement of Reliability Standards
• Develop datasets, reports, and tools in addition to reliability and
performance assessments, to provide independent perspective
• We cover 14 states, 2 provinces, and part of Baja Mexico

4. IS THIS A POPULARITY CONTEST?

5. WHAT IS A GRAPH DATABASE?
• Nodes & Edges
– Nodes represent an entity
– Edges represent relationships
– Unidirectional: From & To
• Nodes & Edges can have properties
• Each database contains a single graph
– All Nodes & Edges are part of the same graph
– Even if they don’t “connect”
– Can be in any schema

6. WHAT ARE GRAPHS GOOD AT?
• Unlike Batman - Relationships
– Query to find out how entities are related
– Search for relationship similarities between entities
– Discover centrality or influence scores among related entities
• Not ideal for questions like
– Search for all entities with a specific attribute
– Aggregate data from entities
– Things relational DBs are already great at
•

7. DEMO – CREATE A GRAPH
CREATE TABLE Meetup
(ID INTEGER PRIMARY KEY, Title VARCHAR(100))
AS NODE;
CREATE TABLE Technology (Tag VARCHAR(100))
AS EDGE;

8. DEMO – POPULATE SOME DATA
INSERT INTO Meetup VALUES(1, 'SLCSQL')
INSERT INTO Meetup VALUES(2, 'UTSPUG')
INSERT INTO Meetup VALUES(3, 'CRMUG')
INSERT INTO Technology VALUES(
(SELECT $node_id FROM Meetup WHERE Title = 'SLCSQL'),
(SELECT $node_id FROM Meetup WHERE Title = 'UTSPUG'),
'Microsoft SQL Server'
)

9. ASCII ART
:MMMMH:
:XMMMM$M$RX
MMM$$MXM!$MX
XMMMMR$MMM!MMX
MMMRMM$$MMX!!MX XMM
<MMMMMMMRMMM!!MM> XMM!
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10. CQL – CYPHER QUERY LANGUAGE
• Not “See-Quel” – that must be some other language
• The MATCH keyword contains all the magic
• Described as ASCII art depicting relationships
– Nodes are just names (or the alias)
– Edges are wrapped in parenthesis
– A dash indicates a relationship
– Relationships can have a direction

11. CQL – GRAMMAR
MATCH (<graph_search_pattern>)
<graph_search_pattern> ::=
{<node_alias> {
{ <-( <edge_alias> )- }
| { -( <edge_alias> )-> }
<node_alias> } }
[ { AND } { ( <graph_search_pattern> ) } ]
[ ,...n ]
<node_alias> ::= node_table_name | node_alias
<edge_alias> ::= edge_table_name | edge_alias

12. CQL EXAMPLES – FRIENDS OF ANDREA
SELECT Person2.Name AS FriendName
FROM Person Person1, Friend, Person Person2
WHERE MATCH(Person1-(Friend)->Person2)
AND Person1.Name = 'Andrea'

13. CQL EXAMPLES – FRIENDS REVERSED
-- Shows the match clause can be reversed
SELECT Person1.Name, Person2.name AS FriendName
FROM Person Person1, friend, Person Person2
WHERE MATCH(Person2<-(friend)-Person1)

14. CQL EXAMPLES – FRIEND OF A FRIEND
SELECT Person1.Name, Person2.Name AS Middle,
Person3.Name AS FoF
FROM People Person1, friend f1, People Person2,
friend f2, People Person3
WHERE MATCH(Person1-(f1)->Person2-(f2)->Person3)

15. CQL EXAMPLES – TWO FRIENDS PART 1
-- Two people who are friends of the same person
SELECT
Person1.name AS Friend1, Person2.name AS Friend2
FROM
Person Person1, friend friend1,
Person Person2, friend friend2,
Person Person0
WHERE MATCH
(Person1-(friend1)->Person0
AND Person2-(friend2)->Person0);

16. CQL EXAMPLES – TWO FRIENDS PART 2
-- Two people who are friends of the same person
SELECT
Person1.name AS Friend1, Person2.name AS Friend2
FROM
Person Person1, friend friend1,
Person Person2, friend friend2,
Person Person0
WHERE MATCH
(Person1-(friend1)->Person0<-(friend2)-Person2);

17. HIERARCHAL QUERIES
• Ah, our dear friend the CTE to the rescue right?
• Wait – aren’t these really a graph structure?
• Let’s look at a simple example

18. INTERESTING QUESTIONS
• Find restaurants that my friends like
– Near where I am currently
• How many coastal cities are rainy?
– How many rainy cities claim to have good fish and chips?
– Are all rainy cities with good fish and chips in Europe?

19. DEMO - GRAPH DB AND POWER BI

20. GRAPH DB LIMITATIONS
• Unidirectional graphs only
• No updating $from_id and $to_id edge columns
– Can update custom columns on edges
– Need to create new edge and delete old one
• No to Temp tables, Table types, table variables
– Cannot be node or edge tables
• No cross-database queries
– Remember? One graph per database

21. BLEEDING EDGE - WHAT IS NEW IN SQL 2019
• Edge Constraints – CONNECTION and TO keywords
Example:
CONSTRAINT MyName CONNECTION
(Customer TO Product)
• MATCH support in MERGE statements
• Use derived table or view aliases in graph match queries

22. WANT TO LEARN MORE?
• Works in Azure SQL and SQL 2017
– Requires correct engine and database level 140
• https://docs.microsoft.com/en-us/sql/relational-
databases/graphs/sql-graph-overview
• Lots of other articles and demos

23. WHAT IS NEXT?

24. QUESTIONS AND ANSWERS
• First the call to action:
– How can you start using this today?
– Any blockers that would stop you?
– Share with others what you learned today
• I’d love to hear your success stories
– Please connect with me on social media
• What questions do you still have?