The document presents an overview of the Entity Attribute Value (EAV) data model by Sandeep Kumar Rout from Mindfire Solutions, detailing its structure, history, and use cases. It explains the components of the EAV model—entities, attributes, and values—as well as the advantages (flexibility, scalability) and disadvantages (performance issues) associated with it. Additionally, it describes the process of indexing to enhance data retrieval performance in an EAV structured database.

1. EAV data model
Presenter: Sandeep Kumar Rout, Mindfire Solutions
Date: 20/03/2014

2. 1/2/12
Presenter: Sandeep Kumar Rout, Mindfire
Solutions
Date: 20/03/2014
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3. 1/2/12
Agenda

Introduction

History

EAV hierarchy structure

Data Retrieve

EAV when to use?

Attribute Set

Pros

Cons Presenter: Sandeep Kumar Rout, Mindfire
Solutions
Date: 20/03/2014

4. 1/2/12
EAV
Entity Attribute Value (EAV) is vertical data
modeling instead of horizontal data modeling
which we regularly use.
In mathematics, this model is known as a
sparse matrix.
EAV is also known as object–attribute–value
model, vertical database model and open
schema.
Presenter: Sandeep Kumar Rout, Mindfire
Solutions
Date: 20/03/2014

5. 1/2/12
EAV History
As a storage method EAV was used in early
object-oriented languages like SIMULA 67.
Functional languages such as LISP have also
use EAV data structure. They contain storage
structures that record object information in
attribute-value pairs – a principle
fundamental to EAV.
Presenter: Sandeep Kumar Rout, Mindfire
Solutions
Date: 20/03/2014

6. 1/2/12
EAV hierarchy structure
EAV hierarchy structure includes these
components:
- Entity : A component with a definitive
existence. Objects are entities. For e.g.
Products, User etc
- Attribute : The fields to which the entities
are related. This are similar to column names
in horizontal data models. Object properties
are attributes
i.e. :- Color, Name, Price etc
Presenter: Sandeep Kumar Rout, Mindfire
Solutions
Date: 20/03/2014

7. 1/2/12
- Value : The value to which entity and
attribute maps to. They are similar to row
value from horizontal database.
Example :- John, $22, blue etc
Presenter: Sandeep Kumar Rout, Mindfire
Solutions
Date: 20/03/2014

8. 1/2/12
Presenter: Sandeep Kumar Rout, Mindfire
Solutions
Date: 20/03/2014

9. 1/2/12
Data Retrieve
Case :-
To get phone no of employee whose id is 1
Basic model :
SELECT phone_no FROM employee WHERE
employee_id = 1;
Presenter: Sandeep Kumar Rout, Mindfire
Solutions
Date: 20/03/2014

10. 1/2/12
Presenter: Sandeep Kumar Rout, Mindfire
Solutions
Date: 20/03/2014
Eav model :
SELECT value FROM employee_int as ei
JOIN employee as e
ON e.employee_id = ei.employee_id
JOIN employee_attribute as ea
ON ea.attribute_id = ei.attribute_id
WHERE e.employee_id = 1 AND
ea.attribute_name = 'phone_no'

11. 1/2/12
EAV when to use?
Presenter: Sandeep Kumar Rout, Mindfire
Solutions
Date: 20/03/2014
Consider a case where there is need to add
new columns or remove new columns on a
regular basis. If using a simple single table it
needs frequent alteration of tables also causes
complexities
With EAV this can be done by simple addition
of a new row in attributes table.
So, generally eav is used in such cases.

12. 1/2/12
Attribute Set
Set of attributes combined to make the entity grouped with
their respective attributes only.
Example :- An online store having books and shirts.
Attributes used by book are different from attributes
used by shirt. So, they can be categorized into attributes
set.
Attribute set Shirt : size, color, price,material, manufacturer
etc
Attribute set Book : pages, author, type of binding,etc
Presenter: Sandeep Kumar Rout, Mindfire
Solutions
Date: 20/03/2014

13. 1/2/12
Pros

Flexible mechanism for attributes to work
with any sort of entities

Scalability – Can change the required data
without changing the structure of database
tables

Independent of hierarchy of data. Less time
to implement Presenter: Sandeep Kumar Rout, Mindfire
Solutions
Date: 20/03/2014

14. 1/2/12
Cons

Performance

EAV don't store value as datatype specific.
Similar type of data are all grouped in one.
As int is generally used to store tinyint,int
etc.

No grouping of entities
Presenter: Sandeep Kumar Rout, Mindfire
Solutions
Date: 20/03/2014

15. 1/2/12
Indexing
This process is used to somehow compensate
the poor performance of EAV structure. It is
not similar to database indexing

This process is time consuming

In this process data from EAV structured
tables are retrieved and store in flat tables

Initially done after all entity types are
generated
Presenter: Sandeep Kumar Rout, Mindfire
Solutions
Date: 20/03/2014

16. 1/2/12

Need to perform this process regularly

Need to be performed on addition, updation
and deletion of data

Makes the data retrieval easier and faster

It completely eliminates old table and
generates new table when re-indexing is
performed.
Presenter: Sandeep Kumar Rout, Mindfire
Solutions
Date: 20/03/2014

17. Question and Answer
Presenter: Sandeep Kumar Rout, Mindfire
Solutions
Date: 20/03/2014

18. Thank you
Presenter: Sandeep Kumar Rout, Mindfire
Solutions
Date: 20/03/2014

19. www.mindfiresolutions.com
https://www.facebook.com/MindfireSolutions
http://www.linkedin.com/company/mindfire-solutions
http://twitter.com/mindfires