Comparative Analysis of Relational And Graph Databases

2012

Abstract: Relational model has been dominating the computer industry since the 1980s mainly for storing and retrieving data. Lately, however, relational database is losing its importance due to its dependence on a rigid schema which makes it difficult to add new relationships between the objects. Another important reason of its failure is that generally, the relational model works best when there are a relatively small and static number of relationships between objects.

Journal of Process Management. New Technologies

Since 1970, relational database models have been in use for storing, manipulating and retrieving data. The importance of relational databases is going to decrease due to the exponential growth of data as it is difficult to work with large number of joining tables. For such kinds of problems, one of the best solutions is to use graph database for storing data. The graph database can be used to store highly connected data. In this article, we are going to put forward a comparison between relational database and graph database with reference to an experiment performed.

International Journal of Recent Technology and Engineering (IJRTE), 2019

Paper Relational database model (also called SQL databases) are one of the prevalent databases that are used with structured data. Currently news demands are arising owing to the magnitude with which the internet and social networks are getting used which brought importance to graph-structured data. Graph database (a nosql database) deal more naturally with highly connected data and are thus becoming popular and efficient choice. Due to limitations faced by relational databases in handling relationships (highly connected data), enterprise information systems find graph database as a promising alternative. According to the form of queries and property of data both relational and graph databases have vitality and flaws. Since most of the data is available in relational schema in this context, the conversion of an application from a relational to a graph format is very beneficial. Thus, this paper develops a dual database system through migration, which unifies the strengths of both re...

Developers, Research Organization and Industries have been using the RDBMS (Relational databases) for many decades. This database technology has been also used by most traditional data-intensive storage applications and data retrieval applications. We generally search data using SQL, which is a declarative query language. RDBMS (Relational databases) are generally considered as most efficient databases but when it comes to high-performance, scalability, flexibility and availability then they are actually not. In current scenario it has been a most interesting thing in data stores that do not use SQL exclusively, can be describe as NOSQL(Stands for Not Only SQL) Movement. We are having many examples such as Google's BigTable, Facebook's Cassandra and Infinite Search and LinkedIn’s Voldemort. Relational Database model has been dominating the computer industry since the 1980s mainly for storing and retrieving data. Lately, however, relational database is losing its importance due to its dependence on a rigid and fixed schema which makes it very difficult to add new relationships in between the various objects. One possible solution can be to shift to the Graph databases Technology as they aspire to overcome various problems like objectivity. This research presents an analysis on a comparison of one such NoSQL graph database called Neo4j with a mostly used relational database system, MySQL, for use as the underlying technology in the development of a software system to store and process data provenance information.

2012 IEEE 28th International Conference on Data Engineering Workshops, 2012

The limitations of traditional databases, in particular the relational model, to cover the requirements of current applications has lead the development of new database technologies. Among them, the Graph Databases are calling the attention of the database community because in trendy projects where a database is needed, the extraction of worthy information relies on processing the graph-like structure of the data. In this paper we present a systematic comparison of current graph database models. Our review includes general features (for data storing and querying), data modeling features (i.e., data structures, query languages, and integrity constraints), and the support for essential graph queries.

Graph database models can be defined as those in which data structures for the schema and instances are modeled as graphs or generalizations of them, and data manipulation is expressed by graph-oriented operations and type constructors. These models took off in the eighties and early nineties alongside objectoriented models. Their influence gradually died out with the emergence of other database models, in particular geographical, spatial, semistructured, and XML. Recently, the need to manage information with graph-like nature has reestablished the relevance of this area. The main objective of this survey is to present the work that has been conducted in the area of graph database modeling, concentrating on data structures, query languages, and integrity constraints.

ACM Computing Surveys (CSUR), 2008

International journal of engineering research and technology, 2012

We report the comparison between the two leading type of Database storage components prevailing in the industry. The Database is largely concerned with managing massive amount of data in a consistent, stable, repeatable and quick manner. The prominent features of both relational as well as non relational databases have been specified which form the basis of the comparison between the two types of database. The relational model is based on mathematical theory(set theory, relational theory) whereas the nonrelational databases may or may not have a single groundwork mathematical theory. Relational model is beneficial when it comes to reliability, flexibility, robustness, scalability requirements but in order to cater to the needs of modern applications where the data is huge and generally unstructured; Non-relational databases show true signs of usability here. Based on the characteristics, commonly used tools of relational and non relational databases are mentioned along with brief in...

Applied Sciences

In developing NoSQL databases, a major motivation is to achieve better efficient query performance compared with relational databases. The graph database is a NoSQL paradigm where navigation is based on links instead of joining tables. Links can be implemented as pointers, and following a pointer is a constant time operation, whereas joining tables is more complicated and slower, even in the presence of foreign keys. Therefore, link-based navigation has been seen as a more efficient query approach than using join operations on tables. Existing studies strongly support this assumption. However, query complexity has received less attention. For example, in enterprise information systems, queries are usually complex so data need to be collected from several tables or by traversing paths of graph nodes of different types. In the present study, we compared the query performance of a graph-based database system (Neo4j) and relational database systems (MySQL and MariaDB). The effect of dif...