This document summarizes a student presentation on NoSQL databases given at the Web Data Management, Search and Retrieval course at Birzeit University in Palestine. The presentation introduces document-oriented databases and compares their structure and querying to relational databases. It also covers concepts like joins, constraints, transactions, embedding documents, and indexing arrays. Benefits of NoSQL databases discussed include scalability, performance, and flexibility in schema design. Specific examples are provided for one-to-many and many-to-many relationships using embedding and references. The presentation concludes with sections on data replication and sharding in MongoDB.

1. Web Data Management, Search and Retrieval Course (MCOM7348)
University of Birzeit, Palestine
January, 2014
Synthesis Paper Talk
Nosql Database
Fayez shayeb
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Master of Computing, Birzeit University
Fayez.aauj@hotmail.com
Master of Computing, Birzeit University
bbbbbbb@yahoo.com
This is a student talk, at the Web Data Management, Search and Retrieval
Course, each student is is asked to present his/her synthesis paper.
Course Page: http://jarrar-courses.blogspot.com/2013/11/web-data-management.html
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2. Document-oriented database
• document-oriented database is a computer
program designed for storing, retrieving, and
managing document-oriented, or semi structured
data, information

3. Comparison
 Document db
 Relational
Article
- id
- authorid
- title
- content
Author
- id
- name
- email
Comment
- id
- articleid
- message
Article
- _id
- title
- content
- author
- _id
- name
- email
- comments[]

4. Concepts
 Joins
 No joins
 Joins at "design time", not at "query time“
 Due to embedded docs and arrays less joins are needed
 Constraints
 No foreign key constraints
 Unique indexes
 Transactions
 No commit/rollback
 Atomic operations
 Multiple actions inside the same document
 Incl. embedded documents

5. Benefits
 Scalable: good for a lot of data / traffic
 Horizontal scaling: to more nodes
 Good for web-apps
 Performance
 No joins and constraints
 Dev/user friendly
 Data is modeled to how the app is going to use it
 No conversion between object oriented > relational
 No static schema = agile

6. One-to-many
 Embedded array / array keys
 Some queries get harder
 You can index arrays!
 Normalized approach
 More flexibility
 A lot less performance
Article
- _id
- content
- tags: {“foo”, “bar”}
- comments: {“id1”, “id2”}

7. many-to-many
 Using array keys
 No join table
 References on both sides
Article
- _id
- content
- category_ids : {“id1”, “id2”}
Category
- _id
- name
- article_ids: {“id7”, “id8”}
 Advantage: simple queries
articles.Where(p => p.CategoryIds.Contains(categoryId))
categories.Where(c => c.ArticleIds.Contains(articleId))
 Disadvantage: duplication, update two docs

8. json
•
•
•
Stands for Javascript Object Notation
Derived from Javascript scripting language
Used for representing simple data
structures and associative arrays
{
{
"_id": "BCCD12CBB",
"type": "person",
"name": "Darth Vader",
"age": 63,
"headware":
["Helmet", "Sombrero"],
"dark_side": true
}
"_id": "BCCD12CBC",
"type": "person",
"name": "Luke",
"age": 35,
"powers":
["Pull", "Jedi Mind Trick"],
"dark_side": false
}

9. Replication
 Only one server is active for writes (the primary, or
master) at a given time – this is to allow strong
consistent (atomic) operations. One can optionally
send read operations to the secondaries when
eventual consistency semantics are acceptable.

10. Sharding
 Sharding is the partitioning of data among multiple
machines in an order-preserving manner.(horizontal
scaling )
Machine 1
Machine 2
Machine 3
Alabama → Arizona
Colorado → Florida
Arkansas → California
Indiana → Kansas
Idaho → Illinois
Georgia → Hawaii
Maryland → Michigan
Kentucky → Maine
Minnesota → Missouri
Montana → Montana
Nebraska → New Jersey
Ohio → Pennsylvania
New Mexico → North Dakota
Rhode Island → South Dakota
Tennessee → Utah
Vermont → West Virgina
Wisconsin → Wyoming

11. Sharding
 The set of servers/mongod process within the shard
comprise a replica set

12. Replication & Sharding conclusion
 sharding is the tool for scaling a system, and
replication is the tool for data safety, high availability,
and disaster recovery. The two work in tandem yet are
orthogonal concepts in the design.

13. Document Databases

14. What is MongoDB?
 Creator: 10 gen, former doublick
 Name: short for humongous (
 Language: C++
)

15. What is MongoDB?
 Defination: MongoDB is an open source, document-
oriented database designed with both scalability and
developer agility in mind. Instead of storing your data
in tables and rows as you would with a relational
database, in MongoDB you store JSON-like
documents with dynamic schemas(schemafree, schemaless).

16. What is MongoDB?
 Goal: bridge the gap between key-value stores (which
are fast and scalable) and relational databases (which
have rich functionality).

17. MongoDB terms ?

18. Term mapping

19. MongoDB Data model
 Data model: Using BSON (binary JSON), developers
can easily map to modern object-oriented languages
without a complicated ORM layer.
 BSON is a binary format in which zero or more
key/value pairs are stored as a single entity.
 lightweight, traversable, efficient

20. Schema design
 RDBMS: join

21. Schema design

22. Schema design

23. Query MongoDB Vs sql?
SQL
mongodb
Create table
db.CreateCollection()
Insert into
db.coll.save()
select
db.coll.find()
update
db.coll.update
delete
db.coll.remove()
drop
db.coll.drop()

24. Query MongoDB Vs sql?

25. Query MongoDB Vs sql?

26. API for MongoDB :
C
C++
C#
Erlang
Haskell
Java
node.js
PHP
Perl
Python
Ruby
Scala (Casbah)

27. Thank You
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