A comparative study of relational database and key-value database for big data applications

Puangsaijai, Wittawat; Puntheeranurak, Sutheera

doi:10.1109/ieecon.2017.8075813

Cited by 20 publications

(14 citation statements)

References 4 publications

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“…We can obtain results by Nested Loops operation. This step is done in memory-based database, because the performance of memory-based database has been certified in [11].…”

Section: Join Algorithmmentioning

confidence: 99%

A Cloud-based Storage and Retrieval Solution for RDF Data

2019

Proceedings of 2019 the 9th International Workshop on Computer Science and Engineering

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In recent years, RDF (Resource Description Framework) has been widely recognized as a standard data storage format. There is a real issue that how to store and retrieve RDF data efficiently, because it is the foundation of all semantic-based application development. In this paper, we propose a novel storage and retrieval solution based on cloud and R*-tree. Different to existing approaches, we use cloud-based storage approach to compress RDF data, meanwhile R*-tree is adapted to retrieve compressed data. The advantage is that it not only reduces the local storage pressure but also improves the retrieval performance compare to existing approaches. Because we separate the storage and retrieval and adapt dictionary-based compression approaches, in terms of security and flexibility, our solution is better than existing approaches.

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“…We can obtain results by Nested Loops operation. This step is done in memory-based database, because the performance of memory-based database has been certified in [11].…”

Section: Join Algorithmmentioning

confidence: 99%

A Cloud-based Storage and Retrieval Solution for RDF Data

2019

Proceedings of 2019 the 9th International Workshop on Computer Science and Engineering

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“…For our specific use case, searching billions of records, scalability to store billions of records was our primary concern. In Puangsaijai2017 [14], we note that MariaDB [15], a MySQL forked project which is feature complete with MySQL [16], shows ETL insert times to be comparable between NoSQL database Redis [17] to be a >20x faster with pipelines over MariaDB [15]. Interesting [14] also shows select operations to be comparable across many simple and complex queries with the exception of 2 simple equals queries.…”

Section: Introductionmentioning

confidence: 99%

“…In Puangsaijai2017 [14], we note that MariaDB [15], a MySQL forked project which is feature complete with MySQL [16], shows ETL insert times to be comparable between NoSQL database Redis [17] to be a >20x faster with pipelines over MariaDB [15]. Interesting [14] also shows select operations to be comparable across many simple and complex queries with the exception of 2 simple equals queries. More interesting are the tested range queries (greater then and less then) [14] shows the NoSQL database to out perform MariaDB by 2x.…”

Section: Introductionmentioning

confidence: 99%

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atSNPInfrastructure, a Case Study for Searching Billions of Records While Providing Significant Cost Savings over Cloud Providers

Harrison

Keleş

Hudson

et al. 2018

2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)

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We explore the feasibility of a database storage engine housing up to 307 billion genetic Single Nucleotide Polymorphisms (SNP) for online access. We evaluate database storage engines and implement a solution utilizing factors such as dataset size, information gain, cost and hardware constraints. Our solution provides a full feature functional model for scalable storage and query-ability for researchers exploring the SNP’s in the human genome. We address the scalability problem by building physical infrastructure and comparing final costs to a major cloud provider.

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“…NoSQL, which remain for "not only SQL" is a contrasting option to relational databases in which information is put in tables. NoSQL databases are particularly valuable for working with huge arrangements of appropriated size and to exhibit the data in a more suitable form [2]. They choose Redis and MongoDB as NoSQL databases because both are robust open source databases.…”

mentioning

confidence: 99%

Performance Evaluation of Redis and MongoDB Databases for Handling Semi-structured Data

Spal¹

2018

IJRASET

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A comparative study of relational database and key-value database for big data applications

Cited by 20 publications

References 4 publications

A Cloud-based Storage and Retrieval Solution for RDF Data

A Cloud-based Storage and Retrieval Solution for RDF Data

atSNPInfrastructure, a Case Study for Searching Billions of Records While Providing Significant Cost Savings over Cloud Providers

Performance Evaluation of Redis and MongoDB Databases for Handling Semi-structured Data

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