NOSQL & SQL database, Slides of Distributed Database Management Systems

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NO-SQL

Dept. Of Computer

Application

Presentation

On:

Content..

 What is SQL..

 What are the shortcoming in SQL

 What is NO-SQL

 How it use to store data

 SQL vs NO-SQL

 Advantages

 Disadvantages

Shortcomings in SQL

◦ (^) Fails to handle big data.

◦ (^) Data models- having a predefines schema.

◦ (^) Data structure- NoSQL handles unstructured data where as SQL

fails to handle it.

◦ (^) No-SQL is Cheaper to manage as compared to SQL.

◦ (^) Scaling- scale out/ horizontal scaling.

◦ (^) Traditional RDBMS uses SQL syntax to store and retrieve data for further insights. Instead, a NoSQL database system

encompasses a wide range of database technologies that can store structured, semi-structured, unstructured and polymorphic

data.

Why No-SQL:

The concept of NoSQL databases became popular with Internet giants like Google, Facebook, Amazon, etc. who deal with huge

volumes of data. The system response time becomes slow when you use RDBMS for massive volumes of data.

◦ (^) To resolve this problem, we could "scale up" our systems by upgrading our existing hardware. This process is expensive.

◦ (^) The alternative for this issue is to distribute database load on multiple hosts whenever the load increases. This method is known

as "scaling out."

NoSQL database is non-relational, so it scales out better than relational databases as they are designed with web applications in

mind.

No-SQL

◦ Stands for “Not only SQL” , provides a mechanism for storage and retrieval of data

and is the next generation database.

◦A non relational database(no tables).

◦It has no specific schema and can handle huge amount of data.

◦A flexible database used for big data and real time web apps.

◦Multiple types of No-SQL databases.

Database

collections

documents

Employee_info

employee

projects

projects

{emp_id:1,e

mp_name:

‘amit’ }

{emp_id:2,e

mp_name:

‘asit’ }

{ proj_id:

102,

Proj_name:

‘proj2’}

{ proj_id:

101,

Proj_name:

‘proj1’}

Types of No-SQL

Wide-column stores:

Wide-column stores organize data tables as columns instead of as rows.

Wide-column stores can be found both in SQL and NoSQL databases.

Wide-column stores can query large data volumes faster than conventional

relational databases. A wide-column data store can be used for recommendation engines, catalogs, fraud detection and

other types of data processing. Google BigTable, Cassandra and HBase are examples of wide-column stores.

Graph stores:

Graph data stores organize data as nodes, which are like records in a relational database, and edges, which represent

connections between nodes. Because the graph system stores the

relationship between nodes, it can support richer representations of data

relationships. Also, unlike relational models reliant on strict schemas, the graph

data model can evolve over time and use. Graph databases are applied in systems that

must map relationships, such as reservation systems or customer relationship management.

Examples of graph databases include Allegro Graph, IBM Graph, Neo4j and Titan.

SQL vs NO-SQL

SQL

1. Type of database: Relational database

2. Schema: pre defined schema

3. Database categories: Table based

4. Complex queries: good fit for complex queries

5. Hierarchical data storage: not as good as NO-SQL as

it uses table structure to store data.

6. Scalability: vertically scalable as it uses RAM,CPU

on a single server.

7. Has a specific language: doesn’t vary from database

to database.

8. Best fit for heavy transactional type application.

9. Mainly used for OLTP(Online Transactional

Processing).

10.Base properties: ACID ( Atomicity, Consistency,

Isolation, Durability)

NO-SQL

1. Non relational database
2. Dynamic schema
3. Document databases , key-value stores , graph stores ,

wide column stores.

4. Not suitable for complex queries
5. Better than SQL as it uses key-value pair way to store

the data.

6. Horizontally scalable as it add more server into the

cluster server.

7. No specific language: varies from database to database.
8. Can be used for transactional type application , But, is

not stable for high load application.

9. Mainly used for OLAP(Online Analytical Processing).

10.Base properties: CAP( Consistency, Availability,

Partition Tolerance )

Disadvantages of NoSQL

• (^) No standardization rules
• (^) Limited query capabilities
• (^) RDBMS databases and tools are comparatively mature
• (^) It does not offer any traditional database capabilities, like consistency when multiple transactions are performed

simultaneously.

• (^) When the volume of data increases it is difficult to maintain unique values as keys become difficult
• (^) Doesn't work as well with relational data
• (^) The learning curve is stiff for new developers
• (^) Open source options so not so popular for enterprises.

Conclusion

◦The basic NoSQL database classifications are only guides. Over time, vendors have mixed and matched

elements from different NoSQL database family trees to achieve more generally useful systems. That

evolution is seen, for example, in MarkLogic, which has added a graph store and other elements to its

original document databases. Couchbase Server supports both key-value and document approaches.

Cassandra has combined key-value elements with a wide-column store and a graph database.

Sometimes NoSQL elements are mixed with SQL elements, creating a variety of databases that are

referred to as multimodel databases.

THANK YOU…THANK YOU…