![Key Value Pair Based
• Data model: (key, value) pairs.
• Designed for processing dictionary.
• Dictionaries contain a collection of
records having fields containing data.
• Records are stored and retrieved
using a key that uniquely identifies
the record,and is used to quickly find
the data with in the database.
• Example: Oracle NoSQL Database,
Riak etc.
• We use it for: storing session
information, user profiles,
preferences , shopping cart data. Key Value Pair
Based[1].](https://image.slidesharecdn.com/presentation1-copy-190113091323/85/introduction-to-NOSQL-Database-12-320.jpg)
![Column based
• It store data as Column families
containing rows that have many
columns associated with a row
key.Each row can have different
columns.
• Column families are groups of
related data that is accessed
together.
• Example:Cassandra, HBase,
Hypertable, and Amazon
DynamoDB.
• We use it for content
management systems ,blogging
platforms, log aggregation.
Column based [1]](https://image.slidesharecdn.com/presentation1-copy-190113091323/85/introduction-to-NOSQL-Database-13-320.jpg)
![Document Based
• The database store send retrieves
documents. It stores documents in
the value part of the key-value
store.
• Self describing, hierarchical tree
data structures consisting of
maps, collections, and scalar
values.
• Example: Lotus Notes ,Mongo
DB, Couch DB, Orient DB, Raven
DB.
• We use it for content management
systems, blogging platforms,
webanalytics,real-timeanalytics e-
commerce applications.
Document Based [1]](https://image.slidesharecdn.com/presentation1-copy-190113091323/85/introduction-to-NOSQL-Database-14-320.jpg)
![Graph Based
• Store entities and relationships
between these entities as nodes
and edges of a graph respectively.
Entities have properties.
• Traversing the relationships is
very fast as relationship between
nodes is not calculated at query
time but is actually persisted as a
relationship.
• Example: Neo4J, InfiniteGraph,
OrientDB, FlockDB.
• It is well suited for connected data
such as social networks ,spatial
data ,routing information for goods
and supply.
Graph Based[1]](https://image.slidesharecdn.com/presentation1-copy-190113091323/85/introduction-to-NOSQL-Database-15-320.jpg)
introduction to NOSQL Database
- 1. Introduction to NOSQL database
- 2. Content • History of database technology • Motivation for Nosql databases • Benefits of Relational databases • Limitations of RDBMS • What is Nosql • CAP Theorm • Types of Nosql • Research Challanges • Conclusion • References
- 3. Summary of early database systems Database name Advantage Limitations Flat file systems • Keep data about a single entity together in a single record. • Can leads to duplicated data and inefficient retrieval. • Difficult to implement security controls to protect confidential data Hierarchical data management systems • Follows parent-child relationships • Stores records in the form of records. searching for a customer in a loan database might require scanning all customer records. Network data management • The ability to represent parent- child and many-to-many relations is an advantage. • Duplicate data, • Difficulty implementing security, Inefficient searching • Difficulty maintaining program • code to access databases Relational Database Management Systems • Store in the form of table. • Normalization • ACID property • SQL • Storage management programs • Memory management programs • Data dictionary • Query language
- 4. Motivations for No SQL Databases • Big data supports storing and querying huge amounts of semi-structured and unstructured data. • e.g Facebook and google stores and process exabyte and zettabyte of data. • So we need databases which can provide: Scalability(Sharding) Cost Flexibility Availability
- 6. Benefits of Relational databases • Based on ACID properties • Strong consistency, concurrency, recovery • Normalization • Standard Query language (SQL) • Vertical scaling (up scaling)
- 7. Limitations of RDBMS Relational databases were not built for distributed applications. Because: • Joins are expensive • Hard to scale horizontally • Expensive (product cost, hardware) The rise of big data (volume,Variety) https://www.slideshare.net/ramakantsoni/p resentation-on-no-sql
- 8. What is NoSQL • It stands for 'NOT ONLY SQL' • #NoSQL was a twitter hashtag for a conference in 2009 used by ERIC EVANS. • There is no strict defination for NoSQL databases. • It is a nonrelational database. • Mainly designed to use for Big Data and Real time web applications.
- 9. Advantages of Nosql over RDBMS • Can handle Semi-structured and unstructured data. • Data Models- No Predefined Schema. • Scaling- Scaling out/ Horizontal Scaling. • Avoids overhead of ACID transactions. • Avoids complexity of SQL query. Source:https://deavid.wordpress.com/2018 /08/29/nosql-databases
- 10. CAP Theorem • Consistency: Clients should read the same data. • Availability: Data to be available all time. • Partial Tolerance: Data to be partitioned across network segments due to network failures. Source:https://www.researchgate.net/figure/CAP- theorem
- 11. NoSQL Types It can be classified into four types: Key Value pair based Column based Document based Graph based Source:https://deavid.wordpress.com/2018/08/29/nosql-databases
- 12. Key Value Pair Based • Data model: (key, value) pairs. • Designed for processing dictionary. • Dictionaries contain a collection of records having fields containing data. • Records are stored and retrieved using a key that uniquely identifies the record,and is used to quickly find the data with in the database. • Example: Oracle NoSQL Database, Riak etc. • We use it for: storing session information, user profiles, preferences , shopping cart data. Key Value Pair Based[1].
- 13. Column based • It store data as Column families containing rows that have many columns associated with a row key.Each row can have different columns. • Column families are groups of related data that is accessed together. • Example:Cassandra, HBase, Hypertable, and Amazon DynamoDB. • We use it for content management systems ,blogging platforms, log aggregation. Column based [1]
- 14. Document Based • The database store send retrieves documents. It stores documents in the value part of the key-value store. • Self describing, hierarchical tree data structures consisting of maps, collections, and scalar values. • Example: Lotus Notes ,Mongo DB, Couch DB, Orient DB, Raven DB. • We use it for content management systems, blogging platforms, webanalytics,real-timeanalytics e- commerce applications. Document Based [1]
- 15. Graph Based • Store entities and relationships between these entities as nodes and edges of a graph respectively. Entities have properties. • Traversing the relationships is very fast as relationship between nodes is not calculated at query time but is actually persisted as a relationship. • Example: Neo4J, InfiniteGraph, OrientDB, FlockDB. • It is well suited for connected data such as social networks ,spatial data ,routing information for goods and supply. Graph Based[1]
- 16. Research Challenges • Transaction Processing : Nosql do not strictly follow ACID properties. • Query Processing: There is no user friendly unified query language for Nosql. • Security: Since follow unstructured data approach along with geographic distribution. Hence its very difficult to apply security.
- 17. Conclusion • RDBMS is a great tool for solving ACID problems • When data validity is super important • When you need to support dynamic queries • NoSQL is a great tool for solving data availability problems • When it’s more important to have fast data than right data • When you need to scale based on changing requirements
- 18. References 1. Ali Davoudian and Liu Chen, Mengchi Liu:A Survey on NoSQL Stores,ACM Comput. Surv. 51, 2, Article,40 (April 2018),43 pages. 2. Dan Sullivan:Nosql for mere Mortals,1st Edition,United States of America:Pearson Education,2015. 3. Xiangdong Huang, Jianmin Wang, Yu Zhong, Shaoxu Song, and Philip S. Yu. 2015:Optimizing data partition for scaling out NoSQL cluster. Concurrency and Computation: Practice and Experience 27, 18, 5793–5809. 4. Katarina Grolinger, Wilson A HigashinoEmail author, Abhinav Tiwari and Miriam AM Capretz:Data management in cloud environments: NoSQL and NewSQL data stores,l. Journal of Cloud Computing: Advances, Systems and Applications,Springer. 2013
- 19. Thank You