NoSQL seminar

1.  NoSQL
05-March-2014
Wednesday
Jainul A. Musani
(MCA,MPhil,MTech)

2. 2

3. 3
What’s Meaning....??
NOT SQL...???

4. 4
Introduction
• Past Decade – DB Professionals dependent
on RDBMS (Relational Database Systems)
and a single standard supported by all
databases : SQL – Structure Query Language
• Relational Model – E.F.Codd’s 1970.

5. 5
Introduction
• RDBMS - Table Oriented
Relational Database for_
•Storage of Data
•Retrieval of Data
5

6. 6
Staff
No
Staff
Name
Post
Salary
Branch
No
Branch
Address
SL21
John White
Manager
30,000
B005
22 Deer Rd,
London
SG37
Ann Beech
Assistant
12,000
B003
163 Main St,
Glasgow
SG14
David Ford
Supervisor
18,000
B003
163 Main St,
Glasgow
SA9
Mary Howe
Assistant
9,000
B007
16 Argyll St,
Aberdeen
SG5
Susan Brand
Manager
24,000
B003
163 Main St,
Glasgow
SL41
Julie Lee
Assistant
9,000
B005
22 Deer Rd,
London
6

7. 7
Introduction
• Relational Model more suitable to ClientServer programming .
• Easier to maintain data and write
programming for Relational Model.
• Predominant technology for storing
structured data in web and business
applications.

8. 8
Introduction
• Relational Model - relies upon hard-and
fast and Structured rules – ACID rules for
database transactions.

9. RDBMS
ACID Rules
Classical Relational Database
Atomic
Consistent
Isolated
Durable

10. 10
A.C.I.D. Properties
Atomic
• A Transaction data modification – either
Completed –or – not perform.
Consistent
• At end of Transaction all data in
consistent state.

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A.C.I.D. Properties
Isolated
• Modification of one data must be
independent of another Transaction.
[other wise outcome of result will be erroneous]
Durable
• When Transaction completed, modification
performed must be permanent in the system.

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A.C.I.D. Properties
12

13. NoSQL
What is
NoSQL?

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What is NoSQL...??
 Non-relational database
management systems,
 Different from traditional
RDBMS in some significant
ways.

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What is NoSQL...??
 Core of NoSQL database_
 Hash Function – mathematical
algorithm – take variable
length of Input and produce a
consistent, fixedlength Output.
 Key/Value pair is stored for
later retrieval of record.

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What is NoSQL...??
 Designed for
 distributed data stores where
 very large scale of data storing
needs
(for example Google or Facebook
which collects terabits of data every
day for their users).

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What is NoSQL...??
 These type of data storing may
not require fixed schema,
avoid join operations and
typically scale horizontally.

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Scaling...!!!!
 Ability of a System to expand
to meet business needs.
Ex. Web application – allow more
people to use web application
 Vertical Scaling
 Horizontal Scaling

19. 19
Vertical Scaling...!!!!
 Scale Up - add more resources
within the same logical unit to
increase capacity.
Ex. Add more CPUs / increase
memory / add more hard drive

20. 20
Horizontal Scaling...!!!!
 Scale Out - add more nodes to
system.
Ex. Add new computer to
distributed software application.
In NoSQL system, data store can be
much faster as it takes advantage
of “scaling out”

21. NoSQL
Term NoSQL
by Carlo Strozzi
Year 1998

22. NoSQL
Why is
NoSQL?

23. 23
Why NoSQL ?
 In today’s time data is
becoming easier to access and
capture through third parties
such as Facebook, Google+ and
others.

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Why NoSQL ?
 Personal user information,
 Social graphs,
 Geo location data,
 User-generated content and
 Machine logging data
are just a few examples where the
data has been increasing
exponentially.

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Why NoSQL ?
 To avail the above service
properly, it is required to
process huge amount of data.
 Which SQL databases were
never designed. The evolution
of NoSql databases is to handle
these huge data properly.

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26

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What’s there in NoSQL ?
 Instead of using structured
tables to store multiple related
attributes in a row, NoSQL
databases use the concept of a
key/value store.

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What’s there in NoSQL ?
 No schema for the database.
 Stores values for each provided
key, distributes them across
the database and then allows
their efficient retrieval.

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What’s there in NoSQL ?
 Lack of a schema prevents
complex queries and
essentially prevents the use of
NoSQL as a transactional
database environment

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RDBMS v/s NoSQL
 Structured and  Stands for Not
organized data
Only SQL
 Structured
 No declarative
query languagequery language
SQL
 No predefined
schema

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RDBMS v/s NoSQL
 Data and its
relationships
are stored in
separate tables.
 Data
Manipulation
Language, Data
Definition
Language
 Key-Value pair
storage, Column
Store, Document
Store, Graph
databases
 Eventual
consistency
rather ACID
property

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RDBMS v/s NoSQL
• Tight
Consistency
• BASE
Transaction
 Unstructured
and
unpredictable
data
 CAP Theorem
 Prioritizes high
performance,
high availability
and scalability

33. NoSQL
CAP
Theorem
(Brewer’s Theorem)

34. 34
CAP Theorem
• When designing any distributed
system. CAP theorem states
that there are three basic
requirements which exist in a
special relation when designing
applications for a distributed
architecture.

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CAP Theorem
• Consistency - the data in the
database remains consistent
after the execution of an
operation. For example after an
update operation all clients
see the same data.

36. 36
CAP Theorem
• Availability - the system is
always on (service guarantee
availability), no downtime.

37. 37
CAP Theorem
• Partition Tolerance - the
system continues to function
even the communication among
the servers is unreliable, i.e.
the servers may be partitioned
into multiple groups that cannot
communicate with one another.

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CAP Theorem
• In theoretically it is impossible
to fulfill all 3 requirements
• CAP provides the basic
requirements for a
distributed system to follow 2
of the 3 requirements

39. 39
CAP Theorem
• CA - Single site cluster, therefore all
nodes are always in contact. When a
partition occurs, the system blocks.
• CP - Some data may not be accessible,
but the rest is still consistent/accurate.
• AP - System is still available under
partitioning, but some of the data
returned may be inaccurate.

40. 40
CAP Theorem
40

41. NoSQL
The BASE
by Eric Brewer

42. 42
The BASE
 The CAP theorem states that a
distributed computer system
cannot guarantee all of the
following three properties at
the same time:
Consistency
Availability
Partition tolerance

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The BASE
 A BASE system gives up on
consistency.
 Basically Available indicates
that the system does guarantee
availability, in terms of the CAP
theorem.

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The BASE
 Soft state indicates that the
state of the system may change
over time, even without input.
This is because of the eventual
consistency model.

45. 45
The BASE
• Eventual consistency indicates
that the system will become
consistent over time, given that
the system doesn't receive
input during that time.

46. 46
ACID v/s BASE
ACID
Atomicity
Consistency
Isolation
Durable
BASE
Basically Available
Soft state
Eventual consistency

47. 47
Pros/Cons - NoSQL
Advantages
High Scalability
Distributed Computing
Lower Cost
Schema Flexibility
Semi-Structured Data
No Complicated Relationship

48. 48
Pros/Cons - NoSQL
Disadvantages
No Standardization
Limited Query Capabilities
Eventual Consistent is not
intuitive to program for

49. NoSQL
Types of
NoSQL

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Categories of NoSQL database
1) Document Oriented:
Data is stored as documents.
An example format may be
like - FirstName="Arun",
Address="St. Xavier's Road",
Spouse=[{Name:"Kiran"}],
Children=[{Name:"Rihit", Age:8}]

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CouchDB, Jackrabbit, MongoDB,
OrientDB, SimpleDB,Terrastore

52. 52
Categories of NoSQL database
2) XML database:
Data is stored in XML
format.
BaseX, eXist, MarkLogic Server
etc.

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Categories of NoSQL database
3) Graph databases:
Data is stored as a collection
of nodes, where nodes are
analogous to objects in a
programming language.
Nodes are connected using
edges.

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AllegroGraph, DEX, Neo4j,
FlockDB, Sones GraphDB

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Categories of NoSQL database
4) Key-value store:
In Key-value-store category of
NoSQL database, an user can
store data in schema-less way.
A key may be strings, hashes,
lists, sets, sorted sets and
values are stored against these
keys.

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Cassandra, Riak, Redis,
memcached, BigTable etc.

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Production deployment
 There is a large number of
companies using NoSQL.
 Google, Facebook, Mozilla,
Adobe, Foursquare, LinkedIn,
Digg, McGraw-Hill Education,
Vermont Public Radio

58. NoSQL
Market &
Business
RoadMap of
NoSQL

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61. NoSQL
That’s All for
NoSQL
Thank You…!!!