NoSQL - 05March2014 Seminar
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The document provides an introduction and overview of NoSQL databases. It discusses: - How NoSQL databases are non-relational and differ from traditional relational databases by not requiring fixed schemas and supporting horizontal scaling. - Examples of different types of NoSQL databases like document stores, key-value stores, and graph databases. - The CAP theorem and eventual consistency of NoSQL databases, which allow high availability and partitioning at the cost of strong consistency. - How NoSQL databases are used by large companies to store rapidly growing unstructured and unpredictable data more efficiently than relational databases.
![11
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.](https://image.slidesharecdn.com/nosql05mar14wed-140305034759-phpapp02/85/NoSQL-05March2014-Seminar-11-320.jpg)
![50
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}]](https://image.slidesharecdn.com/nosql05mar14wed-140305034759-phpapp02/85/NoSQL-05March2014-Seminar-50-320.jpg)
NoSQL - 05March2014 Seminar
- 1. NoSQL 05-March-2014 Wednesday Jainul A. Musani (MCA,MPhil,MTech)
- 2. 2
- 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.
- 11. 11 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.
- 14. 14 What is NoSQL...?? Non-relational database management systems, Different from traditional RDBMS in some significant ways.
- 15. 15 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.
- 16. 16 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).
- 17. 17 What is NoSQL...?? These type of data storing may not require fixed schema, avoid join operations and typically scale horizontally.
- 18. 18 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
- 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.
- 24. 24 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.
- 25. 25 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.
- 26. 26 26
- 27. 27 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.
- 28. 28 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.
- 29. 29 What’s there in NoSQL ? Lack of a schema prevents complex queries and essentially prevents the use of NoSQL as a transactional database environment
- 30. 30 RDBMS v/s NoSQL Structured and Stands for Not organized data Only SQL Structured No declarative query languagequery language SQL No predefined schema
- 31. 31 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
- 32. 32 RDBMS v/s NoSQL • Tight Consistency • BASE Transaction Unstructured and unpredictable data CAP Theorem Prioritizes high performance, high availability and scalability
- 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.
- 35. 35 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.
- 38. 38 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.
- 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
- 43. 43 The BASE A BASE system gives up on consistency. Basically Available indicates that the system does guarantee availability, in terms of the CAP theorem.
- 44. 44 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
- 50. 50 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}]
- 51. 51 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.
- 53. 53 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.
- 54. 54 AllegroGraph, DEX, Neo4j, FlockDB, Sones GraphDB
- 55. 55 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.
- 56. 56 Cassandra, Riak, Redis, memcached, BigTable etc.
- 57. 57 Production deployment There is a large number of companies using NoSQL. Google, Facebook, Mozilla, Adobe, Foursquare, LinkedIn, Digg, McGraw-Hill Education, Vermont Public Radio
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- 61. NoSQL That’s All for NoSQL Thank You…!!!