1. Object-relational mismatch makes the object-oriented "round object" into the relationship-oriented "square table" is so difficult and laborious , but this can be avoided .

2. The static, rigid, inflexible nature of the relational model makes it very difficult to change schemas to meet changing business needs. For the same reason, databases often drag their feet when development teams want to apply agile software development.

3. The relational model is poorly suited to express semi-structured data -- and industry analysts and researchers agree that semi-structured data is the next big thing in information management.

4. Networks are a very efficient structure for storing data. It is no coincidence that the human brain is a huge network and the World Wide Web is similarly constructed as a web. The relational model can express web-oriented data, but it is very weak in its ability to traverse the web and extract information.

While Neo is a relatively new open source project, it is already in use in products with more than 100 million nodes, relations, and attributes, and meets the robustness and performance needs of the enterprise:

Full support for JTA and JTS, 2PC distributed ACID transactions, configurable isolation levels, and large-scale, testable transaction recovery. These are more than just lip service: Neo has been used in highly requested 24/7 environments for over 3 years. It is mature, robust, and fully meets the deployment threshold.

Graph: a network that is a collection of trees in a data principle.

Neo4j is an embedded, disk-based, fully transactional Java persistence engine that stores data in graphs (networks) rather than tables.Neo4j provides massive scalability, handling billions of nodes/relationships/attributes in graphs on a single machine, which can be scaled up to run in parallel on multiple machines. Relative to relational databases, graph databases are adept at handling large amounts of complex, interconnected, and low-structured data that changes rapidly and requires frequent queries - in relational databases, these queries result in a large number of table joins and therefore performance problems.Neo4j focuses on solving the problem of having a large number of connections to the performance degradation that occurs with queries in traditional RDBMSs. By modeling data around a graph, Neo4j traverses nodes and edges at the same rate, with no relation to the amount of data that makes up the graph. In addition, Neo4j provides very fast graph algorithms, recommender systems, and OLAP-style analytics, all of which are not available in current RDBMS systems.

There is a lot of curiosity about Neo because of its use of a "web-oriented database". In this model, domain data is expressed in a "node space" -- a network of nodes, relationships, and attributes (key-value pairs) as opposed to the traditional model of tables, rows, and columns. Relationships are first-level objects that can be annotated by attributes, while attributes indicate the context in which nodes interact. The network model is a perfect match for problem domains that are essentially inherited relationships, such as semantic Web applications.The creators of Neo found that inherited and structured data did not fit well into the traditional relational database model: