Abstract
NoSQL database systems have emerged and developed at an accelerating rate in the last years. Attractive properties such as scalability and performance, which are needed by many applications today, contributed to their increasing popularity. Time is very important aspect in many applications. Many NoSQL database systems do not offer built in management for temporal properties. In this paper, we discuss how we can embed temporal properties in NoSQL databases. We review and differentiate between the most popular NoSQL stores. Moreover, we propose various solutions to modify data models for embedding bitemporal properties in two of the most popular categories of NoSQL databases (Key-value stores and Column stores). In addition, we give examples of how to represent bitemporal properties using Redis Key-value store and Cassandra column oriented store. This work can be used as basis for designing and implementing temporal operators and temporal data management in NoSQL databases.
Highlights
Relational database management systems (RDBMS) were and still dominant in the market of database management systems because of the services they provide such as transaction processing and the well-established structure
The flexible data models offered by these systems in contrast to the strict rigid structure of RDBMS and the continues need for data availability encouraged the use of NoSQL databases [3]
In order to solve the aforementioned issues, this paper discusses bitemporal properties and proposes different variants to help embed the bitemporal characteristics in NoSQL databases
Summary
Relational database management systems (RDBMS) were and still dominant in the market of database management systems because of the services they provide such as transaction processing and the well-established structure. They depend on a set of simple operations and do not follow the strict relational databases design principles. The flexible data models offered by these systems in contrast to the strict rigid structure of RDBMS and the continues need for data availability encouraged the use of NoSQL databases [3]. Google was the leader in adopting these systems by instituting BigTable [6] in 2006, followed by Dynamo [7], which was introduced by Amazon in 2007 Properties such as the ability to scale rapidly, performance, continuous availability and partition tolerance overcome the historical satisfaction of relational database model.
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