2017•Unpublished venueRequires access

Supporting schema evolution in schema-less NoSQL data stores

Loup Meurice, Anthony Cleve

Open publisher page 11 citations

Abstract

NoSQL data stores are becoming popular due to their schema-less nature. They offer a high level of flexibility, since they do not require to declare a global schema. Thus, the data model is maintained within the application source code. However, due to this flexibility, developers have to struggle with a growing data structure entropy and to manage legacy data. Moreover, support to schema evolution is lacking, which may lead to runtime errors or irretrievable data loss, if not properly handled. This paper presents an approach to support the evolution of a schema-less NoSQL data store by analyzing the application source code and its history. We motivate this approach on a subject system and explain how useful it is to understand the present database structure and facilitate future developments.

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What this paper is about

NoSQL data stores are becoming popular due to their schema-less nature. They offer a high level of flexibility, since they do not require to declare a global schema. Thus, the data model is maintained within the application source code. However, due to this flexibility, developers have to struggle with a growing data structure entropy and to manage legacy data. Moreover, support to schema evolution is lacking, which may lead to runtime errors or irretrievable data loss, if not properly handled. This paper presents an approach to support the evolution of a schema-less NoSQL data store by analyzing the application source code and its history. We motivate this approach on a subject system and explain how useful it is to understand the present database structure and facilitate future developments.

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OpenAlex reports 11 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

NoSQL data stores are becoming popular due to their schema-less nature. They offer a high level of flexibility, since they do not require to declare a global schema. Thus, the data model is maintained within the application source code. However, due to this flexibility, developers have to struggle with a growing data structure entropy and to manage legacy data. Moreover, support to schema evolution is lacking, which may lead to runtime errors or irretrievable data loss, if not properly handled. This paper presents an approach to support the evolution of a schema-less NoSQL data store by analyzing the application source code and its history. We motivate this approach on a subject system and explain how useful it is to understand the present database structure and facilitate future developments.

Key concepts: NoSQL, Computer science, Schema evolution, Schema (genetic algorithms), Database schema, Conceptual schema, Database, Information retrieval

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