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  • Graph Databases, NOSQL, and Neo4j
Of the  many different datamodels, the relational model has been dominating since the 80s, with implementations like Oracle, MySQL and MSSQL – also known as Relational Database Management System (RDBMS). Lately, however, in an increasing number of cases the use of relational databases leads to problems both because of Deficits and problems in the modeling of data and constraints of horizontal scalability over several servers and big amounts of data. There are two trends that bringing these problems to the attention of the international software community:
  1. The exponential growth of the volume of data generated by users, systems and sensors, further accelerated by the concentration of large part of this volume on big distributed systems like Amazon, Google and other cloud services.
  2. The increasing interdependency and complexity of data, accelerated by the Internet,  Web2.0, social networks and open and standardized access to data sources from a large number of different systems.
The relational databases have increasing problems to cope with these trends. This has led to a number of different technologies targeting special aspects of these problems, which can be used together or alternatively to the existing RDBMS – also know as Polyglot Persistence. Alternative databases are nothing new, they have been around for a long time in the form of e.g.  Object Databases (OODBMS), Hierarchical  Databases (e.g. LDAP) and many more. But during the last few years a large number of new projects have been started which together are known under the name NOSQL-databases. This article aims to give an overview of the position of Graph Databases in the NOSQL-movement. The second part is an introduction to Neo4j, a Java-based Graph Database.    

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