Priority-Driven Differentiated Performance for NoSQL Database-as-a-Service

Andreoli, Remo; Cucinotta, Tommaso; Oliveira, Daniel Bristot de

doi:10.1109/tcc.2023.3292031

Cited by 4 publications

(1 citation statement)

References 33 publications

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“…The Cloud Provider intends to offer database services that are able to control the response time for specific customers. Popular databases that are widely used may be adapted to enable differentiated per-user/request performance on a priority basis through CPU scheduling and the synchronization mechanisms available within the operating system [27].…”

Section: Related Workmentioning

confidence: 99%

Performance Analysis and Improvement for CRUD Operations in Relational Databases from Java Programs Using JPA, Hibernate, Spring Data JPA

Bonteanu,

Tudose

2024

Applied Sciences

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The role of databases is to allow for the persistence of data, no matter if they are of the SQL or NoSQL type. In SQL databases, data are structured in a set of tables in the relational database model, grouped in rows and columns. CRUD operations (create, read, update, and delete) are used to manage the information contained in relational databases. Several dialects of the SQL language exist, as well as frameworks for mapping Java classes (models) to a relational database. The question is what we should choose for our Java application, and why? A comparison of the most frequently used relational database management systems, mixed with the most frequently used frameworks should give us some guidance about when to use what. The evaluation is conducted based on the time taken for each CRUD operation to run, from thousands to hundreds of thousands of entries, using the possible combinations in the relational database system and the framework. Aiming to assess and improve the performance, the experiments included the possibility of warming-up the Java Virtual Machine before the execution of queries. Also, the research investigated the time spent using different methods of code to determine the critical regions (bottlenecks). Thus, the conclusions provide a comprehensive overview of the performances of Java applications accessing databases depending on the suite decisions considering the database type, the framework in use, and the type of operation, with clear comparisons between the alternatives, the key findings of the advantages and drawbacks of each of them, and supporting architects and developers in their technological decisions and improving the speed of their programs.

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Section: Related Workmentioning

confidence: 99%

Performance Analysis and Improvement for CRUD Operations in Relational Databases from Java Programs Using JPA, Hibernate, Spring Data JPA

Bonteanu,

Tudose

2024

Applied Sciences

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A Novel Approach of Latency and Energy Efficiency Analysis of IIoT With SQL and NoSQL Databases Communication

Kenitar,

Arioua,

Yahyaoui

2023

IEEE Access

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Industrial Internet of Things (IIoT)-enabled production facilities generate vast amounts of data, which, if harnessed effectively, can substantially enhance manufacturing efficiency through latency reduction. The selection of the appropriate data storage technology is a pivotal consideration in achieving this objective. While prior studies have examined SQL and NoSQL databases in terms of latency and energy efficiency, these evaluations have not been conducted specifically within the context of IIoT. This paper aims to fill this research gap by conducting a rigorous comparison of SQL and NoSQL databases, focusing on their performance latency and energy efficiency when interfaced with IoT nodes. By elucidating these relationships, our research offers actionable insights that can guide IIoT-enabled manufacturing facilities in optimizing their operations. Specifically, the paper aids in the selection of the most suitable database technology, thereby contributing to latency minimization and efficiency maximization in industrial settings.

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Inducing Huge Tail Latency on a MongoDB deployment

Andreoli,

Cucinotta

2023

2023 IEEE International Conference on Cloud Engineering (IC2E)

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The NoSQL paradigm has emerged as the leading design choice for cloud providers offering highly scalable storage services. Contrary to traditional relational databases, NoSQL architectures are capable of ingesting the ever-growing volume of nowadays' data-driven applications characterized by low-latency and high-throughput requirements. However, it is difficult to build an ultra-scalable, high-performance storage engine that can sustain an arbitrary number of concurrent clients. A common technique to increase throughput is minimizing the OS overhead, quantified as the number of context switches, through busy waiting (or "spinning"). While this simple synchronization mechanism proves to be beneficial in the high-performance computing community, it requires special care to avoid wasting resources and counter-intuitive behaviors. In this paper, we address an instance of "unsafe" busy waiting in WiredTiger, the underlying storage engine of MongoDB, which leads to a consistent, excessive increase of tail latency in high contention scenarios.

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Priority-Driven Differentiated Performance for NoSQL Database-as-a-Service

Cited by 4 publications

References 33 publications

Performance Analysis and Improvement for CRUD Operations in Relational Databases from Java Programs Using JPA, Hibernate, Spring Data JPA

Performance Analysis and Improvement for CRUD Operations in Relational Databases from Java Programs Using JPA, Hibernate, Spring Data JPA

A Novel Approach of Latency and Energy Efficiency Analysis of IIoT With SQL and NoSQL Databases Communication

Inducing Huge Tail Latency on a MongoDB deployment

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