1. NOSQL

2. NOSQL Not Only SQL 4 Categories More than the traditional database
Document Based
Key Value Based
Column-based
Graph-based

3. Uses for NoSQL

4. Why NOSQL Google Mail, Yahoo Mail Facebook/Instagram
Last volume of users, s as well as large storage need
SQL system provides too many services
Structured data might be too restrictive
Facebook/Instagram
Millions of users submitting posts
Images
Videos
Posts
Limited users can see these posts

5. Google – Big Table Written in Java
Maps to row key and column key and a timestamp
Sparse, distributed multi-dimensional stored map
Scalable into the petabyte range with hundreds or thousands of machines
Bases for Hbase on HDFS

6. Amazon - DynamoDB Used for Amazon cloud service
This is key-value data store

7. Facebook - Cassandra
Supports both key-valued stores and column-bases system

8. NOSQL Family Tree
Clustrix.com

9. Characteristics of NOSQL Systems
Scalability
Horizontal or vertical
NOSQL - horizontal scalability
Vertical – adding storage
Need to be able to extend vertically while system online
Availability, Replication and eventual Consistency
Data is backed up in multiple nodes
Update is difficult over multiple node
Consistency is delayed

10. Characteristics of NOSQL Systems cont.
Replication Models
Master – Slave
Master – Master
Sharding of Files
Horizontal partitioning
File are spread between multiple nodes.
High-Performance Data Access
Hashing
Key fore fast access

11. NOSQL Data Model Not Requiring a Schema Less Powerful Query Language
semi-structured, self describing data
Less Powerful Query Language
Via Program API
CRUD operation – Create, Read , Update, Delete
SCRUD operation – Search, Create, Read , Update, Delete
Versioning
Storage of multiple versions of data

12. CAP Theorem
Consistency (among replicated copies) – consistency of data stored in multiple node, but necessarily other consistency.
Availability (for read and write) – either read or write is processed or error message is sent
Partition Tolerance (Nodes are partitioned due to network fault)

13. MongoDB

14. MongoDB

15. MongoDB

16. MongoDB