• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.934-941
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• 2018

There are some limits on cost and efficiency for large amount of data in RDBMS, and NoSQL is starting to gain popularity. In medical institutions, data forms are different between organizations, and that makes difficulty for interoperability between organizations. In this paper we focused on performance issues between RDMBS and NoSQL in medical documents. We had built two different environment and had experiment comparative analysis of NoSQL with RDBMS based on medical data. We used medical HL7 FHIR as a medical data standard. Also YCSB benchmark tool was used for performance comparison. Experiments shows that NoSQL has better performance in large amounts of medical data processing systems that have over 10,000~100,000 records.

• Journal of KIISE
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• v.43 no.12
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• pp.1385-1395
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• 2016

In the era of Big Data, NoSQL databases provide solutions for problems, circumventing the limitations of traditional relational databases by using new architectures and data model. Contrary to relational database products, the range of the features architectures, and limitations of NoSQL databases is very broad. Thus, choosing the right database products requires more considerations and difficulties. The advent of NoSQL does not only promote the abundance of NoSQL products, but also stimulates the relational database realm to expand their features beyond the relational model. In order to understand NoSQL trends more accurately, here we discuss and compare NoSQL databases with relational databases. We also present the newest features associated with NoSQL in one of the most advanced open-source relational databases, PostgreSQL. To discuss future directions for PostgreSQL we analyzed the performance of NoSQL and PostgreSQL by conducting experiments using the NoSQL benchmark tool (YCSB).

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.6
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• pp.1305-1317
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• 2019

Although encryption for data protection is essential in the big data platform environment of public institutions and corporations, much performance verification studies on encryption algorithms considering actual big data workloads have not been conducted. In this paper, we analyzed the performance change of AES, ARIA, and 3DES for each of six workloads of big data by adding data and nodes in MongoDB environment. This enables us to identify the optimal block-based cryptographic algorithm for each workload in the big data platform environment, and test the performance of MongoDB by testing various workloads in data and node configurations using the NoSQL Database Benchmark (YCSB). We propose an optimized architecture that takes into account.

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.459-460
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• 2019

최근 데이터베이스에서 다루는 데이터의 크기가 커짐에 따라 SQL DB 대신 NoSQL DB의 사용이 증가하고 있다. 이런 변화에 따라 NoSQL과 저장장치에 대한 벤치마킹 및 분석을 통한 저장장치 성능 최적화 및 성능 평가 방법 개선이 필요하다. 본 논문에서는 기존 벤치마킹 툴의 조작 불편함을 해소하기 위해서 사용자의 편의성을 고려한 간편한 벤치마킹 시스템 GUI를 설계한다. 시각화 툴을 활용하여 벤치마킹 결과의 분석을 용이하게 할 수 있는 환경을 제공해준다.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.133-136
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• 2019

본 고에서는 약 100 만건의 건강정보를 이용하여 3-Node MongoDB 플랫폼 환경에서 AES, 3DES, ARIA 암호 알고리즘을 이용하여 암호화를 적용하는 방법을 알아본다. 각각의 암호 알고리즘별로 YCSB 성능테스트 툴을 이용하여 다양한 Workload 별로 성능을 테스트를 수행한 뒤, 그 결과를 비교·정리한다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.298-305
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• 2016

Various NoSQL databases are more excellent to process a large amount of big data than existing relational databases such as MySQL, PostgreSQL and Oracle. Among widely used NoSQL databases, performance of HBase, Cassandra, MongoDB and Redis was comparatively assessed. For distributed processing of a large amount of data, 12 servers were connected through switching hub and Ubuntu was installed as operating system. As for benchmark tool, YCSB was applied. Read and update ratios changed from 50% and 50%, 95% and 5% and finally, 100% and 0% and each of them was assessed as 200,000 commands developed into 1,200,000 commands for each case. Cassandra was most excellent with transaction processing per second while MongoDB was most excellent with the number of processes carried out per unit time.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.198-208
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• 2021

ArangoDB is a NoSQL database system that has been popularly utilized in many applications for storing large amounts of data. In order to apply a new NoSQL database system such as ArangoDB, to real work environments we need a benchmarking system that can evaluate its performance. In this paper, we design and implement a ArangoDB based benchmarking system that measures a kernel level performance well as an application level performance. We partially modify YCSB to measure the performance of a NoSQL database system in the cluster environment. We also define three real-world workload types by analyzing the existing materials. We prove the feasibility of the proposed system through the benchmarking of three workload types. We derive available workloads in ArangoDB and show that performance at the kernel layer as well as the application layer can be visualized through benchmarking of three workload types. It is expected that applicability and risk reviews will be possible through benchmarking of this system in environments that need to transfer data from the existing database engine to ArangoDB.