Presented on November 22, 2014 @ SQLSaturday #350 in Winnipeg, MB Canada Graph databases are used to represent graph structures with nodes, edges and properties. Neo4j, an open-source graph database is reliable and fast for managing and querying highly connected data. Will explore how to install and configure, create nodes and relationships, query with the Cypher Query Language, importing data and using Neo4j in concert with SQL Server... Providing answers and insight with visual diagrams about connected data that you have in your SQL Server Databases! Session Level: Intermediate

1. Graph Databases for SQL Server
Professionals
Stéphane Fréchette

2. Who am I?
My name is Stéphane Fréchette
SQL Server MVP | Consultant | Speaker | Database & BI Architect | NoSQL.
Drums, good food and fine wine. Founder @ukubu, @GatineauOuverte,
@TEDxGatineau
I have a passion for architecting, designing and building solutions that
matter.
Twitter: @sfrechette
Blog: stephanefrechette.com
Email: stephanefrechette@ukubu.com
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3. Thanks to Our Sponsors!
Gold
Silver
Bronze

4. Session Outline
 What is a Graph?
 What is Neo4j?
 Data Modeling – The Property Graph
 Cypher Query Language
 Importing Data…
 Use Cases
 Demos
 Resources
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5. What is a Graph?
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6. Are these Graphs?
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7. This is a Graph
Node
Relationship
A Property Graph
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8. Organization Project Graph
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9. Twitter Social Graph
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10. What is Neo4j?
An open-source graph database by Neo
Technology. Neo4j stores data in nodes
connected by directed, typed
relationships with properties on both,
also know as a Property Graph
 Fully ACID compliant
 Massively scalable, up to several billion
nodes/relationships/properties
 Highly-available, when distributed across
multiple machines
 Accessible by a convenient REST
interface or an object-oriented Java API
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11. Data Modeling
From SQL Server to Graph
Property Graph
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12. Example: Meetup Data In SQL Server
Member MeetupOrganizer MeetupMember Meetup
ID Member
1 Daniel
2 Stephane
3 John
4 Randy
ID Name
1 Ottawa SQL Server User
Group
2 Ottawa JavaScript
3 Ottawa Visio User Group
4 Ottawa Tableau User Group
5 Dirty Dancing Ottawa
MemberID MeetupID
2 1
1 2
3 3
2 4
3 5
MemberID MeetupID
3 1
3 2
4 2
4 4
1 5
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13. Example: Meetup Data In a Graph Member Meetup
name: ‘Stephane’
name: ‘Ottawa Tableau User Group’
name: ‘Ottawa SQL Server User
Group’
name: ‘John’
name: ‘Ottawa JavaScript’
name: ‘Ottawa Visio User Group’
name: ‘Dirty Dancing Ottawa’
name: ‘Randy’
name: ‘Daniel’
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14. Cypher Query Language
Cypher is a declarative graph query language that allows
for expressive and efficient querying and updating of the
graph store
 Pattern-matching
 Declarative: what to retrieve, not how to retrieve it
 Inspired from other known Language (SQL, SPARQL, Haskell, Python)
 Aggregation, Ordering, Limit
 Update the Graph
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15. Cypher and T-SQL
Cypher also has a number of keywords that have a direct
equivalence with SQL which makes it a curiously familiar
language
 WHERE
 ORDER BY
 LIMIT
 SUM, COUNT, STDEVP, MIN, MAX etc…
 LTRIM, UPPER, LOWER, REPLACE, LEFT, RIGHT, SUBSTRING
 DISTINCT
 CASE (SQL Server Pros) – [:WILL_LOVE] -> (Cypher)
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16. Cypher - Meetup
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17. Neo4j Browser
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18. Demo
(let’s query some data…)
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19. Importing Data…
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20. Importing Data…
Some important considerations…
Different import scenarios
 Dataset size: 1000s, 100000s, 10000000s
 Dataset format (source): Database, File (CSV, Spreadsheet, GraphML, Geoff),
Service, Other
 Import type: Initial Bulk Load, Incremental Load, Initial Bulk Load + Incremental Load
Different import tools
 Spreadsheet based
 Neo4j-shell based: (Cypher, neo4j-shell-tools, Cypher LOAD CSV)
 Command-line based: Batch Importer
 Neo4j Brower based
 ETL Tools: (Talend, Mulesoft, Pentaho Kettle)
 Custom software: (Java API, REST API, Spring Data Neo4j)
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21. Many different mappings
Import
Scenarios
Import
Tools
Not always clear what you should be using
Depends on your skillsets, dataset size… (lots of other stuff)
Choose wisely!
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22. Demo
(walkthrough on importing data…)
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23. The Sample Dataset
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24. Importing using Spreadsheets
Very small size datasets < 1000, easy to use
Format data in
spreadsheet
Generate Cypher
statements with
formulas
Copy and Execute
Cypher in Neo4j
browser
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25. Importing using Spreadsheets
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26. Importing using neo4j-shell-tools
Small to medium size datasets
https://github.com/jexp/neo4j-shell-tools
Format data in CSV
files
Create import-cypher
commands
for
neo4j-shell-tools
Execute commands
from neo4j-shell
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27. Importing using neo4j-shell-tools
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28. Importing using LOAD CSV
Native Cypher
Format data in
CSV files
Create
“LOAD CSV”
commands
Execute
command from
neo4j-shell or
browser
Additional
“cleanup” for
Labels and
RelTypes
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29. Importing using LOAD CSV
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30. Importing using Batch Importer
Non-transactional import, suited for very very large datasets
Format data in
TSV files
Execute Batch
Import
command
Copy store
files to Neo4j
Server
directory
Start Neo4j
Server with
generated store
files
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31. Use Cases
Principal uses of Graph Database include:
 Network and Data Center Management
(Queries: Impact Analysis, Root Cause Analysis, Quality-of-Service Mapping, Asset Management)
 Authorization and Access
(Queries : Access Management, Interconnected Group Organization, Provenance)
 Social
(Queries : Friend Recommendations, Sharing & Collaboration, Influencer Analysis)
 Geo
(Queries : Routing, Logistics, Capacity Planning)
 Recommendations
(Queries : Product, Social, Service, and Professional Recommendations)
 Fraud Detection
http://www.neotechnology.com/neo4j-use-cases/
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32. Summary
(graphs)-[:ARE]->(everywhere)
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33. Resources
 Neo Technology http://www.neotechnology.com/
 Neoj.org (Learn, Develop, Downloads,…)
http://www.neo4j.org/
 Neo4j on Vimeo http://vimeo.com/neo4j
 Neo4j on SlideShare http://www.slideshare.net/neo4j
 Neo4j on Github https://github.com/neo4j
 Neo4j Cypher Cheat Sheet http://docs.neo4j.org/refcard/2.1/
 Neo4j Graph Database as a Service
http://www.graphenedb.com/
 Linkurious – The easiest way to explore graph databases
http://linkurio.us/
 KeyLines- Visualize dynamic networks http://keylines.com/
 Experiments with NEO4J: Using a graph database as a SQL
Server metadata hub http://bit.ly/V2PrxN
 Kenny Bastani http://www.kennybastani.com/
 Rik Van Bruggen http://blog.bruggen.com/
 Max de Marzi http://maxdemarzi.com/
 Better Software Development http://jexp.de/blog/
 Graph Databases (Free Book) http://graphdatabases.com/
 Neo4j GraphGist http://gist.neo4j.org/
 GraphConnect Conference http://graphconnect.com/
 Titan – Distributed Graph Database
https://thinkaurelius.github.io/titan/
 InfiniteGraph http://www.infinitegraph.com/
 OrientDB http://www.orientechnologies.com/
 Cayley by Google https://github.com/google/cayley
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34. What Questions Do You
Have?
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35. Thank You
For attending this session
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