The document discusses various types of databases, focusing on graph databases and their advantages over traditional databases like key-value and document stores. It highlights the importance of relationships between data, the challenges of joins in conventional databases, and presents OrientDB as a powerful multi-model NoSQL database that efficiently manages relationships with index-free adjacency. Additionally, it emphasizes the scalability, flexibility, and ease of use of graph databases for connected data.

1. Graph Databases & OrientDB
Arpit Poladia

2. Data and relationships
• Data by itself has
little value.
• It is the
relationships
between the data
that gives it
incredible value.
Order #134
(Order) Croma
(Provider)
Keyboard
(Product)
Raj
(Customer)
Monitor 40”
(Product)
Mouse
(Product)
GameZone
(Provider)
(Sells)
(Has)(Makes)
(Sells)(Has)
(Sells)
(Has)

3. Key-Value databases
Document databases
Column family databases
Graph databases
NoSQL Primer

4. Key-Value databases
Data Model:
• Global key-value mapping
• Big scalable HashMap
Examples:
• Redis, Riak
Pros:
• Simple data model
• Scalable
Cons:
• Create your own foreign keys
• Poor for complex data

5. Document databases
Data Model:
• A collection of documents
• A document is a key value
collection
Examples:
• CouchDB, MongoDB
Pros:
• Simple, powerful data model
• Scalable
Cons:
• Poor for interconnected data
• Query limited to keys and indexes

6. Column family databases
Data Model:
• A big table, with column
families
Examples:
• HBase, HyperTable, Cassandra
Pros:
• Supports Semi-Structured Data
• Naturally Indexed (columns)
• Scalable
Cons:
• Poor for interconnected data

7. Graph databases
Data Model:
•Nodes and Relations
Examples:
•Neo4j, OrientDB
Pros:
•Powerful data model
•Easy to query
Cons:
•Sharding
•Scales UP reasonably well

8. Representing relations
What are the problems with JOIN?
Why NoSQL products avoid relations?
Why graph relations rock!

9. Rings a bell?
ID Name
10 Ned
11 Theon
24 Arya
28 Jon
ID Address
10 24
10 33
32 44
ID Location
24 Winterfell
33 Riverrun
18 Pyke
18 Eyrie
44 Dorne
Customer CustomerAddress Address

10. Problem with JOIN
• A JOIN means searching for a key in another table.
• Indexing the key speeds up searches, but slows down
insert, updates and deletes.
• So in the best case a JOIN is a lookup into an index.
This is done per single join.
• If you traverse hundreds of relationships, you’re
executing hundreds of JOINs.

11. • Index algorithms are all similar and based on
balanced trees.
• This lookup took 5 steps. With millions of
indexed records, the tree depth could be 1000s
of levels!
• Joins are executed every time you cross
relationships. Query performance suffers as
the database increases in size.
Index Lookup
A-Z
A-L M-Z
E-L
E-G H-L
H-L
H-J K-L
A-L
A-D E-L
Leo

12. A better way to manage relations?
A graph database is any storage system
that provides index-free adjacency

13. Graph Theory
Crash Course

14. A very simple graph
Anderson Red pill
Chooses

15. Weighted Graph
Labeled Graph
Property Graph
Different kinds of graph
Undirected Graph
Directed Graph
Pseudo Graph
Multi Graph

16. Property Graph
• All vertices and edges have
unique identifiers.
• Both vertices and edges can have
properties.
• Edges are directed.
• An edge connects only 2 vertices .
• Multiple edges are used to
represent 1-N and N-M
relationships.
Los
Angeles
Population : 3M
Arnold
Quote : I’ll be
back

17. Graph database
A graph database is any storage system
that provides index-free adjacency

18. Features of graph databases
• A database with an explicit graph structure.
• Each node knows its adjacent nodes.
• Optimized for connections and traversing connected data.
• Creates the relationship just once when the edge is
created.
• Traversing time is not affected by database size.
• As the number of nodes increases, the cost of a local step
(or hop) remains the same.

19. OrientDB
2nd generation, multi-model
(graph, document and key-value engines)
NoSQL database

20. How does OrientDB manage relations?
out : [#14:1]
label : ‘Customer’
name : ‘Anderson’
RID = #13:1
RID = #14:1
RID = #13:2
in: [#14:1]
label = ‘Product’
name = ‘Red pill’
out: [#13:1]
in: [#13:2]
label : ‘Chooses’
Anderson
Chooses
Red pill
The RID is the
physical position
The RID of the edge
is stored as out
The RID of the edge
is stored as in
The RID of the vertices are
stored as out and in

21. Features
• Supports fast “lightweight edges”.
• Fully object oriented – classes with properties and inheritance.
• Can store up to 400,000 records per second.
• Supports users and roles with fine grained privileges.
Permissive and commercial friendly Apache 2 license.

22. Schema hybrid
Schema-less mode : Schema is not mandatory.
• Relaxed model, collect heterogeneous documents all together.
Schema-full mode: Schema with constraints on fields and validation rules.
• Customer.age > 17
• Customer.address not null
• Customer.surname is mandatory
• Customer.email matches 'b[A-Z0-9._%+-]+@[A-Z0-9.-]+.[A-Z]{2,4}b'
Schema-mixed mode:
• Schema with mandatory and optional fields + constraints.

23. ACID
db.begin();
try {
// your code
...
db.commit();
} catch (Exception e) {
db.rollback();
}
Complex types
• Supports all basic types like bool,
int, long, double, datetime, string,
binary, decimal etc.
• Supports complex types like List,
Set, Map, Link List, Link Map etc.
• Supports embedded documents.
• Supports custom data types.

24. Scalability
• High Availability
• Auto-Discovery
• Multi-Master Replication
• Synchronous, Asynchronous
and Read-Only replication
• Sharding
Master
Node
Master
Node
C
C C C
CC
C
Auto-
Discovered
Node

25. Extended SQL
Extended SQL which is similar to SQL.
Easy to pick up and easy to use.
• Relations - select from Account where address.city.country.name = ‘Italy’
• Strings - select from City where country.name.substring(1,3).toUpperCase()
= ‘TAL’
• Regex - select from Agenda where email matches ‘bA-Z0-9._%+-?+@A-Z0-9.-
?+.A-Z?{2,4}b’
• Schemaless - select from Profile where any() like ‘%Jay%’
• Collections - select from Tree where children contains ( married = true )

26. Demo
OrientDB Studio

27. Meta graphs
Decorate graph with additional information
to make retrieval faster

28. Location meta graph
Hotel
2
Hotel
1City
Bengaluru
City
Mysuru
Hotel
3
State
Karnataka
Country
India

29. Time based meta graph
Trip
2
Trip
3
Day
12
Trip
1Day
5
Month
March
Year
2016

30. Summing up…
• Graph databases allow you to tell a story. They allow you to
connect the dots.
• Graph databases offer simplicity and speed while permitting
relations to maintain a first-class status.
• Graph databases are designed to store connected data and
make it easy to make sense of that data.
• Graph databases make it easy to evolve the data set.

31. Thank You!
Any questions?