IJRTI
International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)

Call For Paper

For Authors

Forms / Download

Published Issue Details

Editorial Board

Other IMP Links

Facts & Figure

Impact Factor : 8.14

Issue per Year : 12

Volume Published : 11

Issue Published : 118

Article Submitted : 21686

Article Published : 8549

Total Authors : 22487

Total Reviewer : 811

Total Countries : 159

Indexing Partner

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Published Paper Details
Paper Title: Snowflake vs RDBMS: Performance Tuning Techniques
Authors Name: Sarvesh kumar Gupta
Download E-Certificate: Download
Author Reg. ID:
IJRTI_204314
Published Paper Id: IJRTI2505296
Published In: Volume 10 Issue 5, May-2025
DOI:
Abstract: As enterprises continue transitioning from traditional on-premise databases to cloud-native platforms, the contrast between performance tuning in relational database systems (RDBMS) and cloud-based solutions like Snowflake has emerged as a critical area of inquiry. This review explores the architectural, strategic, and operational differences in tuning techniques between these platforms. It presents comparative insights from case studies, performance benchmarks, and peer-reviewed literature. The findings reveal that while traditional RDBMS rely on manual indexing, execution plans, and hardware-bound strategies, Snowflake emphasizes elasticity, clustering, and virtual compute scaling. The paper also proposes a theoretical framework for adaptive tuning and discusses future research directions including AI-driven automation, hybrid platform strategies, and energy-efficient tuning.
Keywords: Snowflake, RDBMS, performance tuning, data warehouse optimization, query optimization, cloud databases, concurrency scaling, virtual warehouses, data engineering, cloud-native computing
Cite Article: "Snowflake vs RDBMS: Performance Tuning Techniques", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 5, page no.c825-c832, May-2025, Available :http://www.ijrti.org/papers/IJRTI2505296.pdf
Downloads: 000410
ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID: IJRTI2505296
Registration ID:204314
Published In: Volume 10 Issue 5, May-2025
DOI (Digital Object Identifier):
Page No: c825-c832
Country: Hayward, California, United States
Research Area: Engineering
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2505296
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2505296
Share Article:

Click Here to Download This Article

Article Preview
Click Here to Download This Article

Major Indexing from www.ijrti.org
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager Academia.edu
arXiv.org : cornell university library Research Gate CiteSeerX DOAJ : Directory of Open Access Journals
DRJI Index Copernicus International Scribd DocStoc

ISSN Details

ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED, Journal Starting Year (ESTD) : 2016

DOI (A digital object identifier)


Providing A digital object identifier by DOI.ONE
How to Get DOI?

Conference

Open Access License Policy

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Creative Commons License This material is Open Knowledge This material is Open Data This material is Open Content

Important Details

Join RMS/Earn 300

IJRTI

WhatsApp
Click Here

Indexing Partner