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Name : v.janaki.
Class: Ii-msc.,computer science.
Batch: 2017-2019.
Incharge staf: ms.m.florance dayana.
 The term NOSQL was first coined by Garlo Strozzi
in 1998 to name his lightweight, open-source, non
relational database that did not expose the
standared SQL interface.
 The term was reintroduced by Eric Evans in early
2009
 NoSQL database are widely used in big data and
other real time web applications
 NoSQL database is used to stock log data which
can then be pulled for analysis.
Where to use NoSQL
Log analysis
Social networking
feeds
Time based data(not
easily analyzed in a
RDBMS)
 NoSQL stands for not Only SQL
 These are non relational,Open source,Distributed
database.
 The adeptness at dealing with a rich variety of data:
Structured
Semi structured
Unstructured data.
NoSQL
No joins
No multi document
transactions
Relaxes one are more ACID
Properties
Non relational data storage
systems
1.NOSQL Database Are Non Relational:
They do not adhere to relational data model.
2.Distributed:
They are distributed meaning the data is
distributed across several nodes in a cluster con
stituted of low cost commodity hardware.
3.No Support For ACID Properties(atomicity
Consistency, Isolation And Durability):
They do not offer support for ACID properties
of transactions.
4.No Fixed Table Schema:
NoSQL databases are becoming increasing
popular owing to their support for flexibility to
the schema.
 We have already stated that NOSQL database are
non relational.
 Classified into the following:
1. key-value or the big hash table
2. schema-less
1.key values:
It maintains a big hash table of keys and values.
For example : Dynamo,Redis
2.Document:
It maintains data in collections constituted of
documents.
For example : MongoDB
Sample document in document data base
{
“Book Name” : ” Fundamentals Of Business Analytics”
“Publisher” : ”Wiley India”
“Year Of Publication” : ”2011”
}
3.Column:
Each storage block has data from only one
column.
For example: Cassandra
NoSQL
Key/value or the big
hash table Amazon
S3(Dynaino)Scalaris.
Schema less
Cassandra(column-
based)
couchDB(document-
based)
Neo4j(graph-based)
Hbase(column-based)
4.Graph:
They are also called network database. A graph
stores data in nodes.
For example: HyperGraphDB.
Label:knows since 2002
Label:knows since 2002 Label:knows since 2002
Label:knows since 2002
ID:1002
Name:jon
Age:32
ID:1001
Name:john
Age:28
ID:1003
Name:group
Age:AAA
1.It has scale out architecture instead of the
monolithic architecture of relational databases.
2.It can house large volumes of structured,semi-
structured and unstructured data.
3.Dynamic schema:
Nosql database allows insertion of data
without a pre defined schema.
4.Auto-sharding:
It automatically spreads data across an
arbitrary number of servers.
The application in question is more often
not even aware of the composition of the server
pool
5.Replication:
It offers good support for replication
which in turn guarantees high availability,fault
tolerance,and disaster recovery.
Thank you

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The big data technology landscape-V.Janaki-II-M.Sc computer Science

  • 1. Name : v.janaki. Class: Ii-msc.,computer science. Batch: 2017-2019. Incharge staf: ms.m.florance dayana.
  • 2.  The term NOSQL was first coined by Garlo Strozzi in 1998 to name his lightweight, open-source, non relational database that did not expose the standared SQL interface.  The term was reintroduced by Eric Evans in early 2009
  • 3.  NoSQL database are widely used in big data and other real time web applications  NoSQL database is used to stock log data which can then be pulled for analysis.
  • 4. Where to use NoSQL Log analysis Social networking feeds Time based data(not easily analyzed in a RDBMS)
  • 5.  NoSQL stands for not Only SQL  These are non relational,Open source,Distributed database.  The adeptness at dealing with a rich variety of data: Structured Semi structured Unstructured data.
  • 6. NoSQL No joins No multi document transactions Relaxes one are more ACID Properties Non relational data storage systems
  • 7. 1.NOSQL Database Are Non Relational: They do not adhere to relational data model. 2.Distributed: They are distributed meaning the data is distributed across several nodes in a cluster con stituted of low cost commodity hardware.
  • 8. 3.No Support For ACID Properties(atomicity Consistency, Isolation And Durability): They do not offer support for ACID properties of transactions. 4.No Fixed Table Schema: NoSQL databases are becoming increasing popular owing to their support for flexibility to the schema.
  • 9.  We have already stated that NOSQL database are non relational.  Classified into the following: 1. key-value or the big hash table 2. schema-less 1.key values: It maintains a big hash table of keys and values. For example : Dynamo,Redis
  • 10. 2.Document: It maintains data in collections constituted of documents. For example : MongoDB Sample document in document data base { “Book Name” : ” Fundamentals Of Business Analytics” “Publisher” : ”Wiley India” “Year Of Publication” : ”2011” }
  • 11. 3.Column: Each storage block has data from only one column. For example: Cassandra NoSQL Key/value or the big hash table Amazon S3(Dynaino)Scalaris. Schema less Cassandra(column- based) couchDB(document- based) Neo4j(graph-based) Hbase(column-based)
  • 12. 4.Graph: They are also called network database. A graph stores data in nodes. For example: HyperGraphDB. Label:knows since 2002 Label:knows since 2002 Label:knows since 2002 Label:knows since 2002 ID:1002 Name:jon Age:32 ID:1001 Name:john Age:28 ID:1003 Name:group Age:AAA
  • 13. 1.It has scale out architecture instead of the monolithic architecture of relational databases. 2.It can house large volumes of structured,semi- structured and unstructured data. 3.Dynamic schema: Nosql database allows insertion of data without a pre defined schema.
  • 14. 4.Auto-sharding: It automatically spreads data across an arbitrary number of servers. The application in question is more often not even aware of the composition of the server pool 5.Replication: It offers good support for replication which in turn guarantees high availability,fault tolerance,and disaster recovery.