Graphical database
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The document discusses graph databases, which use graph theory to store and query relationships. It defines a graph database as a collection of nodes and edges representing connections between nodes. The document outlines advantages like performance and flexibility, disadvantages like immaturity, and applications in fields like bioinformatics and social networks. Current research discussed includes NASA using graph databases for documents and improving graph theory solutions. Future work aims to use graph databases for data-driven decisions and interconnect previously separate data.
Graphical database
- 1. Presented by: Mohsina Mehjabeen (13)
- 2. Contents Introduction Problem defination Advantages and Disadvantages Applications Current Research Future Work Conclusion References
- 3. Introduction A graph database also called as graph-oriented database, is a type of NO SQL database that uses graph theory to store, map and query relationships.
- 4. Problem definition A graph database is essentially a collection of nodes and edges Each node represents a connection or relationship between two nodes. There are two important properties of Graph Database technologies Graph Storage Graph Processing Engine
- 5. Advantages of using Graph Database Performance Flexibility Agility
- 6. Disadvantages of Graph Database It is a growing technology that will be mature in a few years, so, we have to bet for one and pray for it becoming successful. There still does not exist a standard query language for graph databases, leading many implementations to be API only.
- 7. Application Bioinformatics Social Networks Enterprise data
- 8. Current Research NASA is increasingly turning towards graph databases to store and map its research document, making it easier for agency employees to find mission critical information, and also to help the agency to prove its worth to the general public. One of the most important challenges for graph databases is how to express graph theories and how to solve them efficiently. So research is going on using semi-joins program and traversal queries to solve these challenges.
- 9. Future Work In graph theory some programmer are trying to implement the data drive and decision. This prediction or way to implement will help to take digital marketing into a different level. As data is interconnected with each other but it is always stored in a flat way so work is implementing on graph database technology where new opportunities and new ways to look at data is changing day by day.
- 10. Conclusion This is an overall summary of the current state of graph databases. Much of the current research in the field is application driven. The future of graph databases resides in the prevalence of one database over another, most likely determined by the enterprise industry and their adoption needs more structure before it can fully be adopted.
- 11. Reference http://www.wikipedia.org/wiki/Graph_database http://www.slideshare.net/graphtheory/ The Current State of Graph Database (Article) by Mike Buerli, Department of Computer Science, Cal Poly San Luis Obispo
- 12. THANK YOU