Slides of my speech at Codemotion 2014 about OrientDB

1. ROME 11-12 april 2014ROME 11-12 april 2014
OrientDB: a Document-Graph Database
ready for the Cloud
OrientDB Committer
OrientDB Academy Coordinator at Orient Technologies LTD
Project Manager at AssetData S.r.l.
Email: l.dellaquila – at – orientechnologies.com
Twitter: @ldellaquila
Luigi Dell’Aquila

2. ROME 11-12 april 2014 - Luigi Dell’Aquila
Relational Databases:
Everybody knows what a TABLE is
Everybody knows SQL

3. ROME 11-12 april 2014 - Luigi Dell’Aquila
These are tables,
Data ARE Tables!

4. ROME 11-12 april 2014 - Luigi Dell’Aquila
These are tables,
Data ARE Tables!

5. ROME 11-12 april 2014 - Luigi Dell’Aquila
These are tables,
Data ARE Tables!

6. ROME 11-12 april 2014 - Luigi Dell’Aquila
But this is not

7. ROME 11-12 april 2014 - Luigi Dell’Aquila
But this is not

8. ROME 11-12 april 2014 - Luigi Dell’Aquila
But this is not

9. ROME 11-12 april 2014 - Luigi Dell’Aquila
But this is not

10. ROME 11-12 april 2014 - Luigi Dell’Aquila
But this is not

11. ROME 11-12 april 2014 - Luigi Dell’Aquila
These are
GRAPHS!

12. ROME 11-12 april 2014 - Luigi Dell’Aquila
And sometimes
Representing them in tables
Can be difficult
And
Inefficient

13. ROME 11-12 april 2014 - Luigi Dell’Aquila
Think about it…

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When you write your code
You have to deal with
Links, References, Pointers

15. ROME 11-12 april 2014 - Luigi Dell’Aquila
When you write your code
You have to deal with
Collections and Maps
(and dynamic data structures!)

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When you write your code
You have to deal with
Nested and complex objects

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When you write your code
You have to deal with
Class hierarchies,
Inheritance, Polymorphism

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Would You Like
A Storage Layer
That Supports ALL
These Conceps
Out Of The Box?

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This is why
Was born
- Luigi Dell’Aquila

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Two data models:
Graph
and
Document

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Classes, not Tables
create class Person
create class Student extends Person
select from Person
Polymorphic query: returns both instances of Person and
Student

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Dynamic schema
create class Person
insert into Person (name, surname) values (“Luigi”,
“Dell’Aquila”)
No need to fully specify the class structure, you can work in
schemaless mode

23. ROME 11-12 april 2014 - Luigi Dell’Aquila
Complex attributes
Update person
set address = {
“street”: “5th Ave”,
“city”: “NY”
},
tags = [“developer”, “artist”, “geek”]
Collections and embedded properties

24. ROME 11-12 april 2014 - Luigi Dell’Aquila
Physical links
(no Join!)
Update person set address.city =
(select from city where name = ‘Rome’)
where name = ‘Luigi’
Select address.city.country.name
from Person where name = ‘Luigi’
Dot notation instead of Join
No need for foreign keys
O(1) computational cost – compared to O(log N) in relational Join

25. ROME 11-12 april 2014 - Luigi Dell’Aquila
The Graph API
(TinkerPop Blueprints)
Traverse out(“Friend”) from
(select from Person where name = ‘Luigi’)
while address.city = ‘Rome’
Find my friends network in my city (friends, firends of frineds,
friends of friends of friends…)
Deep traversal, no need to know in advance HOW deep

26. ROME 11-12 april 2014 - Luigi Dell’Aquila
Every record has unique ID
Select from Person
{"result": [
{
"@rid": "#13:0",
"@class": “Person",
"name": "Luigi",
"surname": "Dell'Aquila",
"friendOf": "#13:1"
}
]}

27. ROME 11-12 april 2014 - Luigi Dell’Aquila
Every record has unique ID
Select from Person
{"result": [
{
"@rid": "#13:0",
"@class": “Person",
"name": "Luigi",
"surname": "Dell'Aquila",
"friendOf": "#13:1"
}
]}

28. ROME 11-12 april 2014 - Luigi Dell’Aquila
Every record has unique ID
Select from Person
{"result": [
{
"@rid": "#13:0",
"@class": “Person",
"name": "Luigi",
"surname": "Dell'Aquila",
"friendOf": "#13:1"
}
]}

29. ROME 11-12 april 2014 - Luigi Dell’Aquila
Record ID (RID)
=
Physical position

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Traversing relationships
=
Following a physical path

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It means:
• Accessing linked data is very efficient
• No calculation *
• Independent from cluster size **
• Deep traversal is allowed and encouraged ***
* In RDMS, a Join is calculated EVERY TIME you execute a query
** RDBS use index-based optimization to speed up joins, but index
access is O(log N), so it depends on data size – what about Big
Data???
*** in RDMS multiple joins are inefficient (would you dare to write a
query with 1000 joins?)

32. ROME 11-12 april 2014 - Luigi Dell’Aquila
But OrientDB
Gives you more!

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Javascript In the Storage
Extend the query language
With you own functions

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Javascript functions
As REST services

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But of course you can use it
from

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90’s are gone
Today you need

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Scalability

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High availability

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Fault tolerance

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Today everybody
(with a little luck)
Can write a killer app
And reach billions of users

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provides:
Replication (Multi Master)
and
Sharding
Also on cloud infrastructures

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HAZELCAST HAZELCAST
HAZELCAST
Multi Master

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Example

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HAZELCAST HAZELCAST
HAZELCAST
Amazon
Elastic
Load
Balancing
+
Auto
Scaling

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HOWTO 1/3
Key pair

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HOWTO 2/3
Security group

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HOWTO 3/3

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http://www.orientechnologies.com
http://www.orientechnologies.com/training
https://github.com/orientechnologies/orientdb/
Job opportunities: jobs@assetdata.it
References

49. ROME 11-12 april 2014ROME 11-12 april 2014
http://www.orientechnologies.com/event/orientdb-
planet-first-conference-orientdb-rome-italy/
OrientDB Planet