NoSQL databases
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The document discusses NoSQL databases, their characteristics, classifications, and advantages, highlighting their growing relevance for processing large-scale data and analytics. It explains the limitations of traditional relational databases and the shift towards NoSQL systems, which are designed to handle massive datasets in a distributed manner. Additionally, it outlines the key types of NoSQL databases, including key-value, document, column-family, and graph databases, and emphasizes the increasing demand for NoSQL expertise in organizations.
NoSQL databases
- 1. NoSQL Database: New Era of Databases for Big data Analytics - Classification, Characteristics and Comparison A B M Moniruzzaman and Syed Akhter Hossain 03/04/14 CSC 8710 1
- 2. Contents • • • • • • • • • • NoSQL databases definition Why NoSQL databases? Characteristics of NoSQL Databases Primary Uses of NoSQL Database Key-Value databases Documents databases Column-Family databases Graph databases Adoption of NoSQL Database Conclusion 03/04/14 CSC 8710 2
- 3. NoSQL Database • NoSQL for Not Only SQL, refers to an eclectic and increasingly familiar group of non-relational data management system • databases are not built primarily on tables, and generally don't use SQL for data manipulation. • NoSQL systems are distributed, non-relational database, designed for large-scale data storage and for massiveparallel data processing across a large number of commodity servers. 03/04/14 CSC 8710 3
- 4. NoSQL Database • They also use non-SQL languages and mechanisms to interact with data. • NoSQL database systems arose alongside major Internet companies, such as Google, Amazon, and Facebook which had challenges in dealing with huge quantities of data • These systems are designed to scale thousands or millions of users doing updates as well as reads, in contrast to traditional DBMSs and data warehouses 03/04/14 CSC 8710 4
- 5. Why NoSQL? • Relational DBMSs have been a successful technology for many years, providing persistence, concurrency control and integration mechanisms. • The need of processing large amount of data changes the direction from scaling vertically to scaling horizontally on clusters. 03/04/14 CSC 8710 5
- 6. Why NoSQL? • NoSQL databases focus on analytical processing of large scale datasets, offering increased scalability over commodity hardware • Organizations that collect large amounts of unstructured data are increasingly turning to nonrelational databases (NoSQL databases). 03/04/14 CSC 8710 6
- 8. Characteristics of NoSQL Databases • Strong Consistency: all clients see the same version of data. • High Availability: Data always available, at least one copy of the requested data even if one of the nodes is down. • Partition-tolerance: the total system keeps its characteristic even when being deployed on different servers 03/04/14 CSC 8710 8
- 9. Characteristics of NoSQL Databases 03/04/14 CSC 8710 9
- 10. Primary Uses of NoSQL Database 1. Large-scale data processing 2. Exploratory analytics on semi-structured data (expert level) 3. Large volume data storage. 03/04/14 CSC 8710 10
- 11. Classification of NoSQL Databases • Key-Value databases • Documents databases • Column Family databases • Graphics databases 03/04/14 CSC 8710 11
- 12. Key-Value Databases • These DMS store items as alpha-numeric identifiers that refer to the keys. Each key has associated values. • The values could be simple text strings or more complex lists and sets • Search only performed against keys, and limited to exact matches. • Search cannot be performed against values 03/04/14 CSC 8710 12
- 14. Key-Value characterstics • The simplicity of Key-Value Store makes them very quick and light. • Highly scalable retrieval of the values needed for application tasks such as retrieving product names. • This is why Amazon use K-V system, Dynamo, in its shopping cart. Dynamo is a highly available key-value storage system. • Example: Dynamo (Amazon), Voldemort (LinkedIn) Redis, BerkeleyDB, Riak 03/04/14 CSC 8710 14
- 15. Pros and Cons • pros: anything can be stored in an aggregate • cons: only key lookup to access the entire aggregate is allowed (no query and part of aggregate retrieval mechanisms) 03/04/14 CSC 8710 15
- 16. Document Database • Designed to manage and store documents. • These documents are encoded in a standard data exchange format such as XML, JSON (Javascript Option Notation) or BSON (Binary JSON). 03/04/14 CSC 8710 16
- 18. Primary Uses • Document databases are good for storing and managing Big Data-size collections of literal documents such as text documents, email messages. 03/04/14 CSC 8710 18
- 19. Pros And Cons • pros: allow structured queries and partial aggregate retrieval based on the fields in the aggregate • cons: imposes a limit on what can be placed in a database 03/04/14 CSC 8710 19
- 20. Column-Family Databases • It consists of a Key-Value pair where the value consists of set of columns. • The column family databases are represented in tables, each key-value pair being a row. • All the related data can be grouped as one family 03/04/14 CSC 8710 20
- 21. Primary Uses 1. Large-scale, batch-oriented data processing: sorting, parsing, conversion : - conversions between hexadecimal, binary and decimal code values. 2. Exploratory and predictive analytics performed by expert statisticians and programmers. 03/04/14 CSC 8710 21
- 23. Graph Databases • Graph databases replace relational tables with structured relational graphs of interconnected key-value pairings. • Graph databases are useful when you are more interested in relationships between data than the data itself and it works perfectly for the social network. • It is optimized for relationship traversing not for querying • Examples: Neo4j, InfoGrid, Sones GraphDB, AllegroGraph, InfiniteGraph 03/04/14 CSC 8710 23
- 25. Adoption of NoSQL Database • Organizations that have massive data storage are looking seriously at NoSQL. • NoSQL Database expert are highly demanded for most of the developing organizations. • The next graph shows job trends of five NoSQL Databases from Indeed.com 03/04/14 CSC 8710 25
- 26. Job Trends of Five NoSQL Databases 03/04/14 CSC 8710 26
- 27. Adoption of NoSQL Database • MongoDB‘s growth means that it has cemented its place as the most popular NoSQL database. • According to LinkedIn profile mentions, The mentions of NoSQL technologies form 45% in LinkedIn profiles. 03/04/14 CSC 8710 27
- 29. Conclusion • Computational and storage requirements of applications such as for Big Data analytics, Business Intelligence and social networking over peta-byte datasets led us to the change from SQL to NoSQL DBs. • This led to the development of horizontally scalable, distributed non-relational No-SQL databases. • MongoDB‘s is the most demanded one. 03/04/14 CSC 8710 29
Editor's Notes
- #8: Enterprise Resourse planning: Customer Relationship management