A graph database (GDB) is a database that uses graph structures for semantic queries with nodes, edges, and properties to represent and store data. A key concept of the system is the graph (or edge or relationship). The graph relates the data items in the store to a collection of nodes and edges, the edges representing the relationships between the nodes. The relationships allow data in the store to be linked together directly and, in many cases, retrieved with one operation. Graph databases hold the relationships between data as a priority. Querying relationships is fast because they are perpetually stored in the database. Relationships can be intuitively visualized using graph databases, making them useful for heavily inter-connected data. Graph databases are commonly referred to as a NoSQL. Graph databases are similar to 1970s network model databases in that both represent general graphs, but network-model databases operate at a lower level of abstraction and lack easy traversal over a chain of edges. The underlying storage mechanism of graph databases can vary. Relationships are a first-class citizen in a graph database and can be labelled, directed, and given properties. Some depend on a relational engine and "store" the graph data in a table (although a table is a logical element, therefore this approach imposes another level of abstraction between the graph database, the graph database management system and the physical devices where the data is actually stored). Others use a key–value store or document-oriented database for storage, making them inherently NoSQL structures. As of 2021, no universal graph query language has been adopted in the same way as SQL was for relational databases, and there are a wide variety of systems, most often tightly tied to one product. Some early standardization efforts lead to multi-vendor query languages like Gremlin, SPARQL, and Cypher. In September 2019 a proposal for a project to create a new standard graph query language (ISO/IEC 39075 Information Technology — Database Languages — GQL) was approved by members of ISO/IEC Joint Technical Committee 1(ISO/IEC JTC 1). GQL is intended to be a declarative database query language, like SQL. In addition to having query language interfaces, some graph databases are accessed through application programming interfaces (APIs). Graph databases differ from graph compute engines. Graph databases are technologies that are translations of the relational online transaction processing (OLTP) databases. On the other hand, graph compute engines are used in online analytical processing (OLAP) for bulk analysis. Graph databases attracted considerable attention in the 2000s, due to the successes of major technology corporations in using proprietary graph databases, along with the introduction of open-source graph databases. One study concluded that an RDBMS was "comparable" in performance to existing graph analysis engines at executing graph queries. (Wikipedia).
this a brief high-level overview of graph databases using only an ipad. in this video we discuss what a graph database is and how it differs from relational databases. this also looks at high level use cases.
From playlist graph databases
Graph Theory: 02. Definition of a Graph
In this video we formally define what a graph is in Graph Theory and explain the concept with an example. In this introductory video, no previous knowledge of Graph Theory will be assumed. --An introduction to Graph Theory by Dr. Sarada Herke. This video is a remake of the "02. Definitio
From playlist Graph Theory part-1
Graph Data Structure 1. Terminology and Representation (algorithms)
This is the first in a series of videos about the graph data structure. It mentions the applications of graphs, defines various terminology associated with graphs, and describes how a graph can be represented programmatically by means of adjacency lists or an adjacency matrix.
From playlist Data Structures
Data structures: Introduction to graphs
See complete series on data structures here: http://www.youtube.com/playlist?list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P In this lesson, we have described Graph data structure as a mathematical model. We have briefly described the concept of Graph and some of its applications. For practice
From playlist Data structures
Graph Theory: 04. Families of Graphs
This video describes some important families of graph in Graph Theory, including Complete Graphs, Bipartite Graphs, Paths and Cycles. --An introduction to Graph Theory by Dr. Sarada Herke. Links to the related videos: https://www.youtube.com/watch?v=S1Zwhz-MhCs (Graph Theory: 02. Definit
From playlist Graph Theory part-1
Graph Theory FAQs: 01. More General Graph Definition
In video 02: Definition of a Graph, we defined a (simple) graph as a set of vertices together with a set of edges where the edges are 2-subsets of the vertex set. Notice that this definition does not allow for multiple edges or loops. In general on this channel, we have been discussing o
From playlist Graph Theory FAQs
Graph Theory: 05. Connected and Regular Graphs
We give the definition of a connected graph and give examples of connected and disconnected graphs. We also discuss the concepts of the neighbourhood of a vertex and the degree of a vertex. This allows us to define a regular graph, and we give some examples of these. --An introduction to
From playlist Graph Theory part-1
What is a Graph? | Graph Theory
What is a graph? A graph theory graph, in particular, is the subject of discussion today. In graph theory, a graph is an ordered pair consisting of a vertex set, then an edge set. Graphs are often represented as diagrams, with dots representing vertices, and lines representing edges. Each
From playlist Graph Theory
Emil Eifrem talks about graph databases why and when to use them and how they are taking over the database world!
From playlist Programming Podcast
Live CEOing Ep 51: RDF and SPARQL in the Wolfram Language
Watch Stephen Wolfram and teams of developers in a live, working, language design meeting. This episode is about RDF and SPARQL in the Wolfram Language.
From playlist Behind the Scenes in Real-Life Software Design
BathRuby 2016 - How NEO4J Saved my Relationship by Coraline Ada Ehmke
How NEO4J Saved my Relationship by Coraline Ada Ehmke Relational databases have come a long way in the past decade, but sometimes complex data models (a map of network infrastructure, or a quantum-entangled network of social relationships) call for a different approach. How can we address
From playlist BathRuby 2016
Graphing Equations By Plotting Points - Part 1
This video shows how to graph equations by plotting points. Part 1 of 2 http://www.mathispower4u.yolasite.com
From playlist Graphing Various Functions
I know Kung Fu! (or neo4j on Rails without jRuby)
"Reality is a graph, embrace it!" Sure graph databases are really cool and have a timestamp dated next week, but do you know when you should actually use one? Sometimes living on the bleeding edge pays off and in this talk, I'll show you how you can simplify your application and model your
From playlist Cascadia Ruby 2012
Emil Eifrem interviewed at Strata Santa Clara 2013
http://strataconf.com/ Emil Eifrem, CEO of Neo Technology interviewed by Mike Hendrickson of O'Reilly Media.
From playlist Strata Conference 2013 (Santa Clara, CA)
7. Kronecker Graphs, Data Generation, and Performance
RES.LL-005 D4M: Signal Processing on Databases, Fall 2012 View the complete course: http://ocw.mit.edu/RESLL-005F12 Instructor: Jeremy Kepner Theory of Kronecker graphs. Database ingest performance and database query performance. Array multiplication performance. License: Creative Common
From playlist MIT D4M: Signal Processing on Databases, Fall 2012
Graph Databases Will Change Your Freakin' Life (Best Intro Into Graph Databases)
## WTF is a graph database - Euler and Graph Theory - Math -- it's hard, let's skip it - It's about data -- lots of it - But let's zoom in and look at the basics ## Relational model vs graph model - How do we represent THINGS in DBs - Relational vs Graph - Nodes and Relationships ## Why us
From playlist GraphQL
Nicole Schweikardt: Databases and descriptive complexity – lecture 1
Recording during the meeting "Spring school on Theoretical Computer Science (EPIT) - Databases, Logic and Automata " the April 11, 2019 at the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by wor
From playlist Numerical Analysis and Scientific Computing
RES.LL-005 D4M: Signal Processing on Databases, Fall 2012 View the complete course: http://ocw.mit.edu/RESLL-005F12 Instructor: Jeremy Kepner Introduction to signal processing applied to graphs. Course outline. Discussion of relevant technologies programming and storage technologies. Cons
From playlist MIT D4M: Signal Processing on Databases, Fall 2012
Elizabeth Ramirez - Graph Database Patterns in Python - PyCon 2015
"Speaker: Elizabeth Ramirez Creating and using models from a graph database can be quite different to the ones used for row/column/document-oriented databases, in the sense that the same query patterns could differ significantly in structure and performance. This session will present how
From playlist Software Development Lectures
Graph Neural Networks, Session 1: Introduction to Graphs
Examples of Graph representation of data Motivation for doing machine learning on Graphs
From playlist Graph Neural Networks (Hands-on)