One of the main resistences of RDBMS users to pass to a NoSQL product are related to the complexity of the model: Ok, NoSQL products are super for BigData and BigScale but what about the model?

1. Switching from the
Relational to the
Graph model
Luca Garulli –
Founder and CEO @NuvolaBase Ltd
Author of OrientDB Doc/Graph DB
Oct 6th 2012 in Barcelona
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www.orientechnologies.com

2. One of the main resistences of
RDBMS users to pass to a NoSQL product
are related to the
complexity of the model:
Ok, NoSQL products are super for
BigData and BigScale
but...
(c) Luca Garulli Licensed under a Creative Commons Attribution-NoDerivs 3.0 Unported License Page 2

3. ...but what about the model?
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4. What is the NoSQL answer
about managing complex domains?
Key-Value stores
Column-Based
Document database
Graph database
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5. CAUTION!
This presentation will not use a
social like domain with
the classic paradigm of
friend-of-friendN
where the graph databases
are already widely used...
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6. ...But rather we will explore how
to think «graphically» with one of the
most common domains in the
enterprise world:
The old-classic CRM* domain
* today in 99% of the cases a RDBMS is used
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7. Every developer knows
the Relational Model,
but who knows the
Graph one?
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8. Back to school:
Graph Theory crash course
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9. Basic Graph
NoSQL
Likes
Luca Matters
conference
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10. Property Graph Model*
Vertices are directed
NoSQL
Luca Matters
Likes
name: Luca
surname: Garulli since: 2012
conference
company: NuvolaBase
editions: [Cologne, Barcelona]
Vertices and Edges
can have properties
* https://github.com/tinkerpop/blueprints/wiki/Property-Graph-Model
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11. Property Graph Model
NoSQL
Luca Matters
conference
An Edge connects 2 vertices:
use multiple vertices to
represents 1-N and N-M
relationships
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12. Property Graph Model
Pere
Luca
Likes Joins
FriendOf
NoSQL
Matters
Katja conference
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13. Compliments, this is your diploma in
«Graph Theory»
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14. Now go back
to our domain:
the CRM
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15. Domain: minimal CRM
Customer Address
Registry system
Order system
Order Stock
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16. Domain: minimal CRM
Customer Address
How does
Relational DBMS
Registry system
manage relationships?
Order system
Order Stock
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17. Relational World: 1-1 Relationships
Customer Address
Id Name Address Id Location
10 Luca 34 34 Rome, London
11 Katja 44 44 Cologne
34 Sylvia 54 54 Rome
56 Mark 66 66 New Mexico
88 Steve 68 68 Palo Alto
JOIN Customer.Address -> Address.Id
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18. Relational World: 1-N Relationships
Customer Address
Id Name Id Customer Location
10 Luca 24 10 Rome
11 Katja 33 10 London
34 Sylvia 44 34 Rome
56 Mark 66 11 Cologne
88 Steve 68 88 Palo Alto
Inverse JOIN Address.Customer -> Customer.Id
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19. Relational World: N-M Relationships
Customer CustomerAddress Address
Id Name Id Address Id Location
10 Luca 10 24 24 Rome
11 Katja 10 33 33 London
34 Sylvia 34 24 44 Rome
56 Mark 66 Cologne
88 Steve 68 Palo Alto
Additional table with 2 JOINs
(1) CustomerAddress.Id -> Customer.Id and
(2) CustomerAddress.Address -> Address.Id
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20. Relational World: N-M Relationships
Customer CustomerAddress Address
Id Name Id Address Id Location
10 Luca 10 24 24 Rome
11 Katja 10 33 33 London
34 Sylvia 34 24 44 Rome
56 Mark 66 Cologne
88 Steve 68 Palo Alto
Additional table with 2 JOINs
(1) CustomerAddress.Id -> Customer.Id and
(2) CustomerAddress.Address -> Address.Id
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21. What‟s wrong with the
Relational Model?
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22. The JOIN is the evil!
Customer CustomerAddress Address
Id Name Id Address Id Location
10 Luca 10 24 24 Rome
11 Katja 10 33 33 London
34 Sylvia 34 24 44 Rome
56 Mark 66 Cologne
88 Steve 68 Palo Alto
These are all JOINs executed
everytime you traverse a
relationship!
relationship
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23. A JOIN means searching for a key in
another table
The first rule to improve performance
is indexing all the keys
Index speeds up searches but slows down
insert, updates and deletes
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24. So in the best case a JOIN is a lookup
into in an index
This is done per single join!
If you traverse hundreds of relationships
you‟re executing hundreds of JOINs
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25. Index Lookup
it is really that fast?
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26. Index Lookup: how does it works?
A-Z
A-L M-Z
Think to an
Address Book
where we have to find
the Luca’s phone number
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27. Index Lookup: how does it works?
A-Z
A-L M-Z
A-L M-Z
A-D E-L M-R S-Z
Index algorithms are all
similar and based on
balanced trees
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28. Index Lookup: how does it works?
A-Z
A-L M-Z
A-L M-Z
A-D E-L M-R S-Z
A-D E-L
A-B C-D E-G H-L
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29. Index Lookup: how does it works?
A-Z
A-L M-Z
A-L M-Z
A-D E-L M-R S-Z
A-D E-L
A-B C-D E-G H-L
E-G H-L
E-F G H-J K-L
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30. Index Lookup: how does it works?
A-Z
A-L M-Z
A-L M-Z
Found!
A-D E-L M-R S-Z
Each lookup takes
A-D E-L
X steps, where X
A-B C-D E-G H-L
grows with the
E-G H-L index size!
E-F G H-J K-L
Luca
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31. An index lookup is executed
for each JOIN
Querying more tables can easily
produce millions of JOINs/Lookups!
Here the rule: more entries
= more lookup steps = slower JOIN
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32. Is there a better way to
manage relationships?
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33. “A graph database is any
storage system
that provides
index-free adjacency”
- Marko Rodriguez
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34. How does GraphDB manage
index-free relationships?
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35. an Open Source (Apache 2)
document-graph NoSQL dbms
supports: transactions, extended-SQL,
Multi-Master replication, etc
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36. OrientDB: traverse a relationship
The Record ID (RID)
is a Physical position
RID = #13:35 RID = #13:100
RID = #14:54
Lives
Luca Rome
out: [#13:35]
in: [#13:100]
out : [#14:54] Label : ‘Lives’ in: [#14:54]
label : ‘Customer’ label = ‘Address’
name : ‘Luca’ name = ‘Rome’
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37. GraphDB handles relationships as a
physical LINK to the record
assigned when the edge is created
on the other side
RDBMS computes the
relationship every time you query a database
Is not that crazy?!
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38. This means jumping from a
O(log N) algorithm to a near O(1)
traversing cost is not more affected
by database size!
This is huge in the BigData age
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39. OrientDB in the Blueprints micro-benchmark,
on common hw, with a hot cache,
traverses 29,6 Millions
of records in less than 5 seconds
about 6 Millions of nodes traversed per sec!
Do not this at home with a
RDBMS*!
*unless you live in the Google‟s server farm
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40. Create the graph in SQL
$luca> cd bin
$luca> ./console.sh
OrientDB console v.1.2.0-SNAPSHOT (www.orientdb.org)
Type 'help' to display all the commands supported.
orientdb> create vertex V set name = „Luca‟, label = „Customer‟
Created vertex #13:35 in 0.03 secs
orientdb> create vertex V set name = „Rome‟, label = „Address‟
Created vertex #13:100 in 0.02 secs
orientdb> create edge E from #13:35 to #13:100 set label = „Lives‟
Created edge #14:54 in 0.02 secs
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41. Create the graph in Java
OGraphDatabase graph = new OGraphDatabase("local:/tmp/db/graph”);
ODocument luca = graph.createVertex();
luca.field(“name", “Luca");
luca.field(“label", “Customer");
ODocument rome = graph.createVertex();
rome.field(“name", “Rome”);
rome.field(“label", “Address”);
ODocument edge = graph.createEdge(luca, rome).field(“label”, “Lives”);
edge.save();
graph.close();
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42. Query the graph in SQL
orientdb> select in[label=„Lives‟].out from V where label = „Address‟
and name = „Rome‟
---+--------+--------------------+--------------------+--------------------+
#| REC ID |label |out |in |
---+--------+--------------------+--------------------+--------------------+
0| 13:35|Luca |[#14:54] | |
---+--------+--------------------+--------------------+--------------------+
1 item(s) found. Query executed in 0.007 sec(s).
orientdb> select * from V where label = „Address‟ AND
in[label=„Lives‟].size() > 0
---+--------+--------------------+--------------------+--------------------+
#| REC ID |label |out |in |
---+--------+--------------------+--------------------+--------------------+
0| 13:100| Rome | |[#14:54] |
---+--------+--------------------+--------------------+--------------------+
1 item(s) found. Query executed in 0.007 sec(s).
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43. Query the graph in Java
OGraphDatabase graph = new OGraphDatabase("local:/tmp/db/graph”);
// GET ALL THE THE CUSTOMER FROM ROME, ITALY
List<ODocument> result = graph.command( new OCommandSQL (
“select in[label=„Lives‟].out from V where label = „Address‟
and name = ?”)
).execute( “Rome”);
for( ODocument v : result ) {
System.out.println(“Result: “ + v.field(“label”) );
}
---------------------------------------------------------------------------------------
Result: Luca
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44. Query vs traversal
Once you‟ve a well connected database
in the form of a Super Graph you can
cross records instead of query them!
All you need is some root vertices
where to start to traverse
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45. Query vs traversal
Special
Customers Stocks
Customers
Luca John Sylvia
White
This is a Soap
root vertex Order Order
2332 8834
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46. Query the graph in SQL
Customers Supposing that the root node #30:0 links all the
#30:0 Customer vertices
Get all the customers:
orientdb> select out.in from #30:0
Get all the customers who bought at least one „White Soap‟ product:
orientdb> select * from (
select out.in from #30:0
) where out.in.out[label=„Bought‟].in.name = „White Soap‟
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47. Demo time!
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48. NuvolaBase.com
The first
Graph Database
on the Cloud
always available
few seconds to setup it
use it from app & mobile
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49. «Graphs change the way of modelling data»
Luca Garulli
Author of CEO at
Document-Graph NoSQL
Open Source project Ltd, London UK
www.twitter.com/lgarulli
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