Neo4j - Connecting the dots

Relation Databases have been around for a very long time. They are rock solid, they offer you a lot of power and flexibility, but often at the price of performance.
What do you do if you have highly connected data, that you need to query, and it has multiple joins and subqueries, and of course you need the results ASAP so long running queries are out of the question?
Well, maybe it is time to look at a graph DB called Neo4j and what it can do for you.
In this talk we will go over the features, possibilities, highs and the lows of Neo4j.

Transcript

1. Neo4j
   connecting the dots
   Code4Hire, 2015, DaFed 1
   

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2. business owner, developer, consultant, mercenary, writing
   terrible code that performs exceptionally, wrangling
   elePHPants and Pythons, obsessed with process automation,
   interested in continuous integration and delivery, clean code,
   testing, best practices and distributed systems
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3. Databases are great,
   Databases are fun,
   Databases make our
   connected world run
   — Vranac
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4. Special cases and snowflakes
   • Storing structured product information?
   Store as a document.
   • Describing how a user got from point A to point B?
   Follow a graph.
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5. NoSQL
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6. 
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7. Nazgûl
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8. Code4Hire, 2015, DaFed 8
   

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9. NO! Squeal!
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10. 
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11. Graph?
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12. 7 Bridges of koenigsburg
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13. From Designer To Developer
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14. Graph Database
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15. Neo4j
    Use Cases:
    • matchmaking
    • network management
    • software analytics
    • scientific research
    • routing
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16. hhhhhhh
    h:::::h
    h:::::h
    h:::::h
    ccccccccccccccccyyyyyyy yyyyyyyppppp ppppppppp h::::h hhhhh eeeeeeeeeeee rrrrr rrrrrrrrr
    cc:::::::::::::::c y:::::y y:::::y p::::ppp:::::::::p h::::hh:::::hhh ee::::::::::::ee r::::rrr:::::::::r
    c:::::::::::::::::c y:::::y y:::::y p:::::::::::::::::p h::::::::::::::hh e::::::eeeee:::::eer:::::::::::::::::r
    c:::::::cccccc:::::c y:::::y y:::::y pp::::::ppppp::::::ph:::::::hhh::::::h e::::::e e:::::err::::::rrrrr::::::r
    c::::::c ccccccc y:::::y y:::::y p:::::p p:::::ph::::::h h::::::he:::::::eeeee::::::e r:::::r r:::::r
    c:::::c y:::::y y:::::y p:::::p p:::::ph:::::h h:::::he:::::::::::::::::e r:::::r rrrrrrr
    c:::::c y:::::y:::::y p:::::p p:::::ph:::::h h:::::he::::::eeeeeeeeeee r:::::r
    c::::::c ccccccc y:::::::::y p:::::p p::::::ph:::::h h:::::he:::::::e r:::::r
    c:::::::cccccc:::::c y:::::::y p:::::ppppp:::::::ph:::::h h:::::he::::::::e r:::::r
    c:::::::::::::::::c y:::::y p::::::::::::::::p h:::::h h:::::h e::::::::eeeeeeee r:::::r
    cc:::::::::::::::c y:::::y p::::::::::::::pp h:::::h h:::::h ee:::::::::::::e r:::::r
    cccccccccccccccc y:::::y p::::::pppppppp hhhhhhh hhhhhhh eeeeeeeeeeeeee rrrrrrr
    y:::::y p:::::p
    y:::::y p:::::p
    y:::::y p:::::::p
    y:::::y p:::::::p
    yyyyyyy p:::::::p
    ppppppppp
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17. Nodes, Relationships,
    Labels, oh my...
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18. Nodes,
    Relationships,
    Labels, oh my...
    CREATE (c:Cake { type: 'Chocolate' }) RETURN c
    CREATE (d:Dessert { season: 'Any' }) RETURN d
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19. Nodes,
    Relationships,
    Labels, oh my...
    MATCH (a:Cake { type: 'Chocolate' }), (b:Dessert { season: 'Any' })
    CREATE (a)-[:IS_TYPE_OF]->(b)
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20. Voilà
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21. Comparative Examples
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22. Find all Products
    SQL:
    SELECT p.*
    FROM products as p;
    Cypher:
    MATCH (p:Product)
    RETURN p;
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23. Field Access, Ordering and Paging
    SQL:
    SELECT p.ProductName, p.UnitPrice
    FROM products as p
    ORDER BY p.UnitPrice DESC
    LIMIT 10;
    Cypher:
    MATCH (p:Product)
    RETURN p.productName, p.unitPrice
    ORDER BY p.unitPrice DESC
    LIMIT 10;
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24. Joining Products with Customers
    SQL:
    SELECT distinct c.CompanyName
    FROM customers AS c
    JOIN orders AS o ON (c.CustomerID = o.CustomerID)
    JOIN order_details AS od ON (o.OrderID = od.OrderID)
    JOIN products as p ON (od.ProductID = p.ProductID)
    WHERE p.ProductName = 'Chocolade';
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25. Joining Products with Customers
    Cypher:
    MATCH (p:Product {productName:"Chocolade"})<-[:PRODUCT]-
    (:Order)<-[:PURCHASED]-(c:Customer)
    RETURN distinct c.companyName;
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26. Hierarchies and Trees, Variable Length Joins
    SQL:
    SELECT p.ProductName
    FROM Product as p
    JOIN ProductCategory pc ON (p.CategoryID = pc.CategoryID AND pc.CategoryName = "Dairy Products")
    JOIN ProductCategory pc1 ON (p.CategoryID = pc1.CategoryID
    JOIN ProductCategory pc2 ON (pc2.ParentID = pc2.CategoryID AND pc2.CategoryName = "Dairy Products")
    JOIN ProductCategory pc3 ON (p.CategoryID = pc3.CategoryID
    JOIN ProductCategory pc4 ON (pc3.ParentID = pc4.CategoryID)
    JOIN ProductCategory pc5 ON (pc4.ParentID = pc5.CategoryID AND pc5.CategoryName = "Dairy Products")
    ;
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27. Hierarchies and Trees, Variable Length Joins
    Cypher:
    MATCH (p:Product)-[:CATEGORY]->(l:ProductCategory)-[:PARENT*0..]-
    (:ProductCategory {name:"Dairy Products"})
    RETURN p.name
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28. Demo Time
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29. The bad & The Ugly
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30. Is that a date or you are just timestamping?
    08/03/2015 @ 2:20pm (UTC) -> 1438611609
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31. Import Data
    CREATE CONSTRAINT ON (deal:Deal) ASSERT deal.id IS UNIQUE;
    USING PERIODIC COMMIT 5000
    LOAD CSV WITH HEADERS FROM
    "file:///Users/vranac/dev/deals/temp/deals_100k.csv" AS row
    WITH row
    MERGE (d:Deal {Id: row.id})
    ON CREATE SET d.Id = row.id,
    d.a = row.a,
    d.b = row.b,
    ON MATCH SET d.a = row.a,
    d.b = row.b,
    ;
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32. Long queries timeout
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33. The End
    Thank You!
    Questions?
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