NOSQL new technoligy in data base

1. Erciyes University
College of Engineering
Department of Computer Engineering
Erciyes University
Graduate school of natural and applied sciences
Department of Computer Engineering
Dr. FEHIM KOYLU
Course name: CENG,500
Subject:
“No SQL DATABASE”
Hudhaifa AL- Khazraji
Student No. 4013031611

2. The contents are :-
 Introduction .
 Overview for (RDBMS) and (SQL) .
 Question for what , why and when (No SQL).
 Advantages and disadvantages (No SQL).
 Categories of (No SQL).
 Current applications of (No SQL).
 Distinguishing Characteristics for (No SQL) .
 Benefits of NoSQL
 Features that differs by the (NO SQL) FOR (RDBMS).
 CAP Theorem (Brewer’s Theorem).
 Future of NoSQL.
 Conclusion.
 References.
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3. Introduction:
Now and in the age of information technology with smart devices
emergence and widespread use in the use of Internet search has
become a data transfer dramatically process as well as websites and
others, We need all this data to the stored in databases designed
and managed by systems where emerged into what is known
databases management systems, including starting Manual systems
down to relational systems using Structure Query Language (SQL)
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4. **System R – IBM research project (1974)
**Ingres – University of California Berkeley (early 1970’s)
**Oracle – Rational Software, now Oracle Corporation (1974)
**SQL/DS – IBM’s first commercial RDBMS (1981)
**Informix – Relational Database Systems, now IBM (1981)
**DB2 – IBM (1984)
**Sybase SQL Server – Sybase, now SAP (1988)
First concept is Relational Database Management Systems
(RDBMS),There are (DBMS) Based on the Relational Model:
Before entering the main topic you should learn some basic concepts
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5. Some example of the types from databases systems :-
Manual database system
(1)
Hierarchical database system
(2)
network database system Relational database system
(4)
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6. The second concept is Structure Query Language (SQL)
SQL is a language for querying relational databases.
History:
Developed at IBM San Jose Research Laboratory, early 1970’s,
for System R
Credited to Donald D. Chamberlin and Raymond F. Boyce
Based on relational algebra and tuple calculus
Originally called SEQUEL
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7. Clauses, expressions, predicates, queries, statements, transactions, operators, nesting
etc.
select o_orderpriority, count(*) as order_count
from orders
where o_orderdate >= date '[DATE]‘ and o_orderdate < date '[DATE]' + interval
'3' month
and exists (select * from lineitem
where l_orderkey = o_orderkey and l_commitdate < l_receiptdate)
group by o_orderpriority
order by o_orderpriority;
Language Elements:
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8. What
why when
NO
SQL
The questions that always arises by developers is :
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9. what IS meant by term (No SQL) ?
It is abridgment to ( Not Only Structures Query Language ), is one of the branches of
databases management system (DBMS) that are working to save and retrieve data
by modeling techniques different from its predecessor in relational databases.
In the beginning , And specifically in 1998, use (Carlo Struts) databases relational
open source, which you don't take the interface of (SQL)that
used in relational data base named is (No Rel),It’s mean non-relational.
Then in 2009, (Eric Evans) use the growing of number from data base ,
And very much for distribution , open source and non-relation
called it (No SQL).
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10. why
Prefer to use (No SQL) ?
We've covered a lot of the general issues you need to be aware of to make
decisions in the new world of NoSQL databases. It's now time to talk about why you
would choose NoSQL databases for future development work. Here are some broad
reasons to consider the use of NoSQL databases.
First reason big data
To improve programmer productivity by using a database that better
matches an application's needs.
To improve data access performance via some combination of handling larger
data volumes, reducing latency, and improving throughput. 5/11/2016
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11. when to use the (No SQL) ?
This set of reasons that are given because when we use the (NO SQL):-
When the huge recovery is the main objective, especially with the potential
of simple servers
 Relationships between the data stored is not important.
 Increasing specific data as in Twitter posts.
data organization or reorganization from time to time.
 Your application is imperative when working speed, so we find (No SQL) in
mobile applications and games and blogging platforms.
 No significant data extraction logic, or that you can deal with this logic
through the application itself after fetching data
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12. These schemes give concept of why and where we use technology
(No SQL):-
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13. Advantages of (No SQL):-
 High scalability
 Distributed Computing
 Lower cost
 Schema flexibility, semi-structure data
 No complicated Relationships
 Follow base of theory (CAP)
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14. Disadvantages of (No SQL):-
 No standardization
 Limited query capabilities (so far)
 Eventual consistent is not intuitive to program for
 Does not deal with campany that need high accuracy to obtain detailed
results especially banks where such companies but avoiding
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15. Categories of (No SQL)
There are most famous in the world
for categories (No SQL):-
1. document store :-
Where the information is stored in
The form of documents classified by
such famous formats (XML, JSON. Etc)
so easy to query the information in
it but without using the Joins and often
Correspond to the nature of the OOP
in organization and classification. 5/11/2016
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16. 2. Key- value Store :
The information is stored depending on the
key and value that put him, from defects
that sometimes we can query the value of a
specific key, but is fast and simple, among
other types of companies working on the
technology Amazon , such as Adopting this
company database (No SQL) technique
(Amazon's Dynamo Paper) that was written
in 2007.
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17. 3. Column Family Stores :
were created to store and process
very large amounts of data distributed
over many machines. There are still keys
but they point to multiple columns.
In the case of BigTable
(Google's Column Family NoSQL model)
, rows are identified by a row key
with the data sorted and stored
by this key. The columns are
arranged by column family.
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18. 4. Graph Databases Stores :
Graph Databases are built with nodes, relationships between notes and the
properties of nodes. Instead of tables of rows and columns and the rigid
structure of SQL, a flexible graph model is used which can scale across
many machines.
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19. Current applications of (No SQL)
 Dynamo: was created by Amazon.com and is the most prominent Key-Value NoSQL database.
Amazon was in need of a highly scalable distributed platform for their e-commerce businesses so
they developed Dynamo. Amazon S3 uses Dynamo as the storage mechanism.
 Cassandra: was open sourced by Facebook and is a column oriented NoSQL database.
 BigTable: is Google's proprietary column oriented database. Google allows the use of Big Table but
only for the Google App Engine.
 SimpleDB: is another Amazon database. Used for Amazon EC2 and S3, it is part of Amazon Web
Services that charges fees depending on usage.
 CouchDB: along with MongoDB are open source document oriented NoSQL databases.
 Neo4J: Neo4j is an open source graph database
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20. Distinguishing Characteristics for (No SQL)
Large data volumes
• Google’s “big data”
 Scalable replication and distribution
• Potentially thousands of machines
• Potentially distributed around the
world
Queries need to return answers
quickly
Mostly query, few updates
Asynchronous Inserts & Updates
Schema-less
ACID transaction properties are not
needed BASE
CAP Theorem
Open source development
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21. Benefits of NoSQL:-
 Continuously Available: A database that stays online even in the face of the most devastating
infrastructure outages.
 Geographically Distributed: Fully active data, everywhere you need it.
 Operationally Low Latency: Response times fast enough for your most intense operational cloud
applications.
 Linearly Scalable: Predictably scale to meet the current and future data needs of cloud
applications.
 Immediately Decisive: Full range of data manipulation capabilities tightly integrated into a single
system.
 Functionally Cohesive: Coherent integration and interoperability of mixed workloads and
multiple data models.
 Operationally Mature: Enterprise-ready data management for cloud applications.
 Low TCO: No requirements for specialized hardware or ancillary software
NoSQL databases are primarily designed for supporting decentralized systems that target cloud
applications. A NoSQL database like Cassandra typically offers the following benefits over other database
management systems
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22. RDBMSNo SQLFeature
Handles Limited Data VolumesHandles Huge Data Volumes
Data Volume
Less GuaranteedHighly GuaranteedData Validity
Horizontally & VerticallyHorizontally
Scalability
Structured Query Language (SQL)No declarative query language
Query
Language
Predefined Schema (Data Definition
Language & Data Manipulation Language)
No predefined schema or less rigid schemasSchema
Supports relational data and its relationships
are stored in separate tables
Supports unstructured and unpredictable dataDataType
Based on ACID principle (Atomicity,
Consistency, Isolation and Durability)
Based on BASE principle (Basically,
Available, Soft State, Eventually Consistent)
ACID/BASE
Features that differs by the (NO SQL) FOR (RDBMS):-
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23. CAP Theorem (Brewer’s Theorem)
 You must understand the CAP theorem when you talk about NoSQL databases or in fact 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:-
 Consistency :-(Coherence): all the nodes or devices have the same information
at the same time (updated).
 Availability :- This means that the system is always on (service guarantee availability), no downtime.
 - Partition Tolerance - This means that the system continues to function even the communication among
the servers is unreliable , the servers may be partitioned into multiple groups that cannot communicate
with one another
 In theoretically it is impossible to fulfill all 3 requirements.
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24.  Therefore all the current NoSQL database follow the different combinations of the C, A, P from the CAP
theorem. Here is the brief description of three combinations CA, CP, AP :
 Consistency and Availability (CA) - Single site cluster, therefore all nodes are always in contact. When a
partition occurs, the system blocks.
 Consistency and Partition Tolerance (CP) - Some data may not be accessible, but the rest is still
consistent/accurate.
 Availability and Partition Tolerance (AP) - System is still available under partitioning, but some of the data
returned may be inaccurate
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26.  organization that have massive data storage needs are looking
seriously at No SQL .
 In a survey conducted by Information Week, 44%
of business IT professionals haven't heard of NO SQL
 Further, only 1% of the respondents reported that NoSQL is a part
of their strategic direction
 Clearly, NoSQL has its place in our connected world but will need to
continue to evolve to get the mass appeal that many think it could
have
Future of NoSQL
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27. Conclusion
All the choice provided by the rise of NoSQL databases does
not mean the demise of RDBMS databases. We are entering an
era of polyglot persistence, a technique that uses different data
storage technologies to handle varying data storage needs.
Polyglot persistence can apply across an enterprise or within a
single application
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28. References :-
 “NoSQL -- Your Ultimate Guide to the Non - Relational Universe!”
http://nosql-database.org/links.html
 “NoSQL (RDBMS)”
http://en.wikipedia.org/wiki/NoSQL
 PODC Keynote, July 19, 2000. Towards Robust. Distributed Systems. Dr. Eric A. Brewer. Professor, UC Berkeley.
Co-Founder & Chief Scientist, Inktomi .
www.eecs.berkeley.edu/~brewer/cs262b-2004/PODC-keynote.pdf
 “Brewer's CAP Theorem” posted by Julian Browne, January 11, 2009.
http://www.julianbrowne.com/article/viewer/brewers-cap-theorem
 “How to write a CV” Geek & Poke Cartoon http://geekandpoke.typepad.com/geekandpoke/2011/01/nosql.html
 “MapReduce: Simplified Data Processing on Large Clusters”, Jeffrey Dean and Sanjay Ghemawat, December
2004.
http://labs.google.com/papers/mapreduce.html
 “Scalable SQL”, ACM Queue, Michael Rys, April 19, 2011
http://queue.acm.org/detail.cfm?id=1971597
 “a practical guide to noSQL”, Posted by Denise Miura on March 17, 2011 at
http://blogs.marklogic.com/2011/03/17/a-practical-guide-to-nosql/
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29. Thank you
for
listening to me
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