This document provides an overview of NoSQL databases. It discusses why cloud data stores became popular due to the rise of social media sites and need for large data storage. NoSQL databases provide a mechanism for storage and retrieval of data that is not modeled in tabular relations. NoSQL databases are scalable, do not require fixed schemas, and lack ACID properties. The document also discusses the CAP theorem, which states that a distributed system cannot achieve consistency, availability, and partition tolerance simultaneously.

1. Presented by:
Chandan Malik (801431006)

2. NO SQL- Non Relational Database
• No SQL provides a mechanism for storage and
retrieval of data that is modelled in means
other than tabular relations.

3. Why Cloud Data Stores
 Explosion of social media sites (Facebook,
Twitter) with large data needs
 Explosion of storage needs in large web sites
such as Google, Yahoo
 Much of the data is not files
 Rise of cloud-based solutions such as Amazon
S3 (simple storage solution)
 Shift to dynamically-typed data with frequent
schema changes

4. Scaling
 Best way to provide ACID and a rich query model is
to have the dataset on a single machine
 RDBMS were not designed to be distributed
 As database grows, rate of number of transactions
per second falls.
 One solution is partitioning of large tables that is to
scale out the database across a cluster of separate
database servers.

5. What is No SQL ?
 Stands for Not Only SQL
 Class of non-relational data storage systems
 Usually do not require a fixed table schema
 Do not use the concept of joins which are expensive
operations.
 Lack ACID ( Atomicity, Consistency, Isolation,
Durability) properties.
 Leading users of NoSQL datastores are social
networking sites such as Twitter, Facebook, LinkedIn
 It's not a replacement for a RDBMS but compliments
it

6. CAP Theorem
 CAP theorem states that it is impossible for any
shared data system to simultaneously hold these
three properties:
1. Consistency ( all nodes see same data at the same
time)
2. Availability ( guarantee that every request receives
a response )
3. Partition ( Partitioning or distributing the
database)
 You can have at most two of these three properties

7. CAP Theorem
 To scale out, you have to partition. That leaves
either consistency or availability to choose from,
Choose a specific approach based on the needs of
the service.
 CAP Theorem states: Strict Consistency can't be
achieved at the same time as availability and
partition-tolerance.
 When no updates occur for a long period of time,
eventually all updates will propagate through the
system and all the nodes will be eventually
consistent

8. BASE
 Scalability and better performance of No SQL is
achieved by sacrificing ACID properties.
 No SQL is having BASE compatibility
BA – Basically available
S – Soft State
E- Eventually consistent
Basically Available - system seems to work all the time
Soft State - it doesn't have to be consistent all the time
Eventually Consistent - becomes consistent at some
later time

9. Types of No Sql databases
1. Key-value data model
2. Document-data model
3. Column family data model
4. Graph data model

10. Key-Value Data model
 It has a Big Hash Table of keys & values

11. Key-Value Data model
 The key can be auto-generated while the value can be
String, JSON, BLOB (basic large object) etc
 This key/value type database allow clients to read and
write values using the key as follows:
1. get(key) -- Extract the value given a key
2. put(key, value) -- Create or update the value given
its key
3. delete(key) -- Remove the key and its associated
value
4. execute(key, operation, parameters) -- Invoke an
operation to the value (given its key) which is a
special data structure (e.g. List, Set, Map .... etc).

12. Key-Value Data model
 Performance is enhanced to a great degree because of
the cache mechanisms that accompany the mappings
 Eg: Amazon DynamoDB is a fully managed
proprietary No SQL database service that is offered
by Amazon.com as part of the Amazon Web
Services portfolio

13. No SQL distinguishing Characteristics
 Suitable for applications that supports large amount of
unstructured data.
 Schema-less
 Do not support Joins
 Do not follow ACID properties
 Scalable
 Data is replicated to multiple nodes (therefore
identical and fault-tolerant) and can be partitioned

14. THANK YOU