2015•Procedia Computer ScienceOpen access

Scalable Database Management in Cloud Computing

Pankaj Deep Kaur, Gitanjali Sharma

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Abstract

The emerging Big Data paradigm, due to technological proliferations, has attracted the attention of many database management solutions. Owing to its variedness, volume and variety it is difficult to gather, transfer and store data while promising good performance in terms of scalability. These challenges call for an exhaustive reviewing of existing data management systems covering the scalability metrics like partitioning, replication, concurrency control and consistency. This paper throws a light into the design decisions chosen by existing scalable db vendors to help analyze any possible modifications to their infrastructure for future applications. Further, scalability metrics have been identified and solutions of three major projects have been compared on the basis of these metrics. Comparison has also been done for open source projects. The paper also broadly discusses the use cases for these open source projects.

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What this paper is about

The emerging Big Data paradigm, due to technological proliferations, has attracted the attention of many database management solutions. Owing to its variedness, volume and variety it is difficult to gather, transfer and store data while promising good performance in terms of scalability. These challenges call for an exhaustive reviewing of existing data management systems covering the scalability metrics like partitioning, replication, concurrency control and consistency. This paper throws a light into the design decisions chosen by existing scalable db vendors to help analyze any possible modifications to their infrastructure for future applications. Further, scalability metrics have been identified and solutions of three major projects have been compared on the basis of these metrics. Comparison has also been done for open source projects. The paper also broadly discusses the use cases for these open source projects.

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Available abstract

The emerging Big Data paradigm, due to technological proliferations, has attracted the attention of many database management solutions. Owing to its variedness, volume and variety it is difficult to gather, transfer and store data while promising good performance in terms of scalability. These challenges call for an exhaustive reviewing of existing data management systems covering the scalability metrics like partitioning, replication, concurrency control and consistency. This paper throws a light into the design decisions chosen by existing scalable db vendors to help analyze any possible modifications to their infrastructure for future applications. Further, scalability metrics have been identified and solutions of three major projects have been compared on the basis of these metrics. Comparison has also been done for open source projects. The paper also broadly discusses the use cases for these open source projects.

Key concepts: Computer science, Scalability, Cloud computing, Concurrency control, Consistency (knowledge bases), Database, Concurrency, Distributed computing

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