What’s the Difference between a Graph Database and a Relational Database?

Graph databases have been gaining popularity over recent years as a viable alternative to the relational model. Graph databases are particularly well suited to storing connected data – data with lots of interconnected relationships, especially those that run many levels deep.

This article looks at the main differences between graph databases and relational databases.

Continue reading

What is a Graph Database?

A graph database is a database that uses a graphical model to represent and store the data.

The graph database model is an alternative to the relational model.

In a relational database, data is stored in tables using a rigid structure with a predefined schema.

In a graph database, there is no predefined schema as such. Rather, any schema is simply a reflection of the data that has been entered. As more varied data is entered, the schema grows accordingly.

Continue reading

What is an ORDBMS?

ORDBMS stands for Object-Relational Database Management System.

An ORDBMS is a database management system that is a hybrid between the object-oriented model (OODBMS) and the relational model (RDBMS).

Each of those two models has their strengths and weaknesses. By combining the two models, a DBMS can take advantage of various strengths from each model.

Continue reading

What is an OODBMS?

OODBMS stands for Object-Oriented Database Management System.

An object-oriented database management system (also known simply as an object database) is a DBMS where data is represented in the form of objects, as used in object-oriented programming.

In contrast to relational database management systems (RDBMSs), where data is stored in tables with rows and columns, an object-oriented database stores complex data and relationships between data directly, without mapping to relational rows and columns.

Continue reading

What is a Data Warehouse?

A data warehouse is a large collection of data that can be used to help an organisation make key business decisions.

Here’s a more precise definition of the term,  as coined by Bill Inmon, (considered by many to be “the father of data warehousing”):

A data warehouse is a subject-oriented, integrated, nonvolatile, and time-variant collection of data in support of management’s decisions.

Continue reading