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The Property Graph Model
Relationships provide directed, named semantically relevant connections between two node-entities. A relationship always has a direction, a type, a start node, and an end node. Like nodes, relationships can have any properties. In most cases, relationships have quantitative properties, such as weights, costs, distances, ratings, time intervals, or strengths. As relationships are stored efficiently, two nodes can share any number or type of relationships without sacrificing performance. Note that although they are directed, relationships can always be navigated regardless of direction.
What is Neo4j ?
Neo4j is an open-source NoSQL graph database implemented in Java and Scala. With development starting in 2003, it has been publicly available since 2007. Neo4j is used today by hundreds of thousands of companies and organizations in almost all industries. Use cases include matchmaking, network management, software analytics, scientific research, routing, organizational and project management, recommendations, social networks, and more. Neo4j Training Hyderabad.
Neo4j implements the Property Graph Model efficiently down to the storage level. As opposed to graph processing or in-memory libraries, Neo4j provides full database characteristics including ACID transaction compliance, cluster support, and runtime failover, making it suitable to use graph data in production scenarios.
Some particular features make Neo4j very popular among users, developers, and DBAs:
Materializing of relationships at creation time, resulting in no penalties for complex runtime queries
Constant time traversals for relationships in the graph both in depth and in breadth due to efficient representation of nodes and relationships
All relationships in Neo4j are equally important and fast, making it possible to materialize and use new relationships later on to “shortcut” and speed up the domain data when new needs arise
Compact storage and memory caching for graphs, resulting in efficient scale-up and billions of nodes in one database on moderate hardware
Written on top of the JVM.
Why and When to use the graph databases?
The graph databases are built upon the graph theory. As you know that there are a lot of real life problems can be formed as a graph which is Nodes, Arcs, and properties of both. If you tried to implement this in RDBMS and you’ll have to develop a very complicated queries while it will be simple if you used the Graph model <breadth or depth search and return paths>. Also besides the fact that the Neo4J is solve most of the RDMS scalability as it is horizontal scalable. Most of the problems that have challenges are the network like problems .. think about the Social like facebook, google .. etc. Can you imagine how to represent some recursive relation into RDBMS ?!! ..
see this comparison for querying RDBM and Neo4j:
for 1000 people:
for 1000000 people: