The ppt explain about basics of graph databases.

1. GGRAPHRAPH
DDATABASEATABASE
Shruti Arya
July 22, 2013

2. Graph Database
GRAPH DATABASE
A graph is a set of nodes
interconnected by links .
A database is an organised
collection of data.

3. A Graph Database is a database that
uses graph structures with nodes,
edges, and properties to represent
and store information.

4. The Graph DB Model

5.  Graph databases are NoSQL databases.
 NoSQL is a data storage technology.
 NoSQL simply means “ NOT ONLY SQL”.

6. NNeed of Grapheed of Graph
DatabaseDatabase //
NoSQLNoSQL

7. IINCREASING SIZE OF DATANCREASING SIZE OF DATA
SETSET
2007 2008
2009
2010
2011?
0
500
1000
1500
2000
2500
3000

8. • Text (content)
• Hyper-Text (added pointers)
• RSS (joined those pointers)
• Blogs (added pingbacks)
• Tagging (grouped related
data)
• RDF (described connected
data)
• GGG (content + pointers
+ relationships +
descriptions)
CCONNECTED-NESSONNECTED-NESS
GGG = Giant global graph

9. SSEMI-EMI-SSTRUCTUREDTRUCTURED IINFORMATIONNFORMATION
 If you tried to collect all the data of every movie ever
made, how would you model it?
 Actors, Characters, Locations, Dates, Costs, Ratings,
Showings, Ticket Sales, etc.
 Need to store more data about each entity

10. AARCHITECTURERCHITECTURE

12. Four NoSQL Quadrants / Categories

15. Key Value Stores: Pros and Cons
Pros:
Simple data model
Scalable
Cons:
Create your own “foreign keys”
Poor for complex data

16. Column Family: Pros and Cons
Pros:
Supports Simi-Structured Data
Naturally Indexed (columns)
Scalable
Cons:
Poor for interconnected data

17. Document Databases: Pros and Cons
Pros:
Simple, powerful data model
Scalable
Cons:
Poor for interconnected data
Query model limited to keys and indexes
Map reduce for larger queries

18. Graph Databases: Pros and Cons
Pros:
Powerful data model, as general as RDBMS
Connected data locally indexed
Easy to query
Cons:
Requires rewiring your brain

19. HHOWOW GGRAPHRAPH DDATABASESATABASES
WWORKORK ??

20. The Graph DB Model

21. “A Graph —records data in→ Nodes —which have→
Properties”
“Nodes —are organized by Relationships —which also have→ →
Properties”

23. Building a Node Space

24. Building a Node Space

25. Defining Relationship Types

26. The Graph DB Model : traversal

28. Traversing a Node Space

29. QQUERYUERY AA GGRAPHRAPH WWITHITH TTRAVERSALRAVERSAL
“A Traversal —navigates→ a Graph; it —identifies→ Paths
—which order→ Nodes”

30. Graph Database Vendors 
 Neo4J (neo4j.org)
 OrientDB (orientechnologies.com)
 Dex
 HyperGraphDB
 Infogrid
 Sones

31. Graph Database Use Cases 
 Clustering  Task Planning
 Social Connections  Scheduling
 Hubs  Process Assignation
 Graph Mining  Routing
 Centrality Measures  Logistics
 Location Based services  League Planning

32. Graph Like Applications
 Recommendations
– Heuristics (Page Rank)
– Local
 Shortest Paths
 Hammock Functions
 Walks
 Search algorithms
 Shooting stars
 K-nearest neighbours
Some of the best-known uses of graph databases include Google’s
Knowledge Graph, Facebook's Social Graph and Twitter’s Interest Graph.

33.  If your database is highly associative
 If your data is NOT used for statistical analysis, data
mining and exploration, or operational research
 If you have large data sets with changing or on-the-
fly schemas
When To Use Graph Databases?

34.  Represent related data as it inherently is. So, developers can start
coding immediately
 Great performance , as graph databases, which are defined as
any storage system that provides index-free adjacency. What this
means is that every element in the database contains a direct link
to its adjacent element, and so no need of joins
 Response time remains constant, not depending on the total
amount of data stored.
Benefits Of Graph Databases?

35. Thank you…. 