Memory Optimization Techniques in Large-Scale Data Management Systems

Siddharth Choudhary Rajesh

New York University, New York

NY 10012, United States

Ajay Shriram Kushwaha

Professor, Sharda university

Abstract – In the era of big data, managing large-scale data systems efficiently has become a critical challenge for organizations and researchers alike. Memory optimization plays a pivotal role in ensuring the performance, scalability, and cost-effectiveness of data management systems. This abstract explores contemporary techniques employed to optimize memory usage in large-scale data environments. It highlights methods such as caching strategies, in-memory computing frameworks, and advanced data compression techniques that reduce storage overhead without compromising data integrity. Additionally, the study delves into memory-aware query processing algorithms and dynamic resource allocation mechanisms that adapt to changing workloads, enabling real-time analytics and reducing latency. The integration of machine learning-based memory management further enhances predictive capabilities, allowing systems to proactively optimize memory allocation. By synthesizing recent advancements and identifying potential challenges, this abstract underscores the importance of memory optimization in driving the efficiency and sustainability of modern data-intensive systems.

Keywords – Memory optimization, large-scale data systems, in-memory computing, caching strategies, data compression, memory-aware algorithms, dynamic resource allocation, machine learning, real-time analytics, data-intensive systems.

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Antony Satya Vivek Vardhan Akisetty, Ashish Kumar, Murali Mohana Krishna Dandu, Prof. (Dr) Punit Goel, Prof. (Dr.) Arpit Jain; Er. Aman Shrivastav. 2023. “Automating ETL Workflows with CI/CD Pipelines for Machine Learning Applications.” Iconic Research And Engineering Journals Volume 7, Issue 3, Page 478-497.
Gaikwad, Akshay, Fnu Antara, Krishna Gangu, Raghav Agarwal, Shalu Jain, and Prof. Dr. Sangeet Vashishtha. “Innovative Approaches to Failure Root Cause Analysis Using AI-Based Techniques.” International Journal of Progressive Research in Engineering Management and Science (IJPREMS) 3(12):561–592. doi: 10.58257/IJPREMS32377.
Gaikwad, Akshay, Srikanthudu Avancha, Vijay Bhasker Reddy Bhimanapati, Om Goel, Niharika Singh, and Raghav Agarwal. “Predictive Maintenance Strategies for Prolonging Lifespan of Electromechanical Components.” International Journal of Computer Science and Engineering (IJCSE) 12(2):323–372. ISSN (P): 2278–9960; ISSN (E): 2278–9979. © IASET.
Gaikwad, Akshay, Rohan Viswanatha Prasad, Arth Dave, Rahul Arulkumaran, Om Goel, Dr. Lalit Kumar, and Prof. Dr. Arpit Jain. “Integrating Secure Authentication Across Distributed Systems.” Iconic Research And Engineering Journals Volume 7 Issue 3 2023 Page 498-516.
Vaidheyar Raman Balasubramanian, Nagender Yadav, Er. Aman Shrivastav. (2024). Streamlining Data Migration Processes with SAP Data Services and SLT for Global Enterprises. Iconic Research And Engineering Journals, 8(5), 842–873.
Jayaraman, S., & Borada, D. (2024). Efficient Data Sharding Techniques for High-Scalability Applications. Integrated Journal for Research in Arts and Humanities, 4(6), 323–351. https://doi.org/10.55544/ijrah.4.6.25.
Srinivasan Jayaraman, CA (Dr.) Shubha Goel. (2024). Enhancing Cloud Data Platforms with Write-Through Cache Designs. International Journal of Research Radicals in Multidisciplinary Fields, 3(2), 554–582. Retrieved from https://www.researchradicals.com/index.php/rr/article/view/146.
Sreeprasad Govindankutty, Ajay Shriram Kushwaha. (2024). The Role of AI in Detecting Malicious Activities on Social Media Platforms. International Journal of Multidisciplinary Innovation and Research Methodology, 3(4), 24–48. Retrieved from https://ijmirm.com/index.php/ijmirm/article/view/154.
Srinivasan Jayaraman, S., and Reeta Mishra. (2024). Implementing Command Query Responsibility Segregation (CQRS) in Large-Scale Systems. International Journal of Research in Modern Engineering and Emerging Technology (IJRMEET), 12(12), 49. Retrieved December 2024 from http://www.ijrmeet.org.
Jayaraman, S., & Saxena, D. N. (2024). Optimizing Performance in AWS-Based Cloud Services through Concurrency Management. Journal of Quantum Science and Technology (JQST), 1(4), Nov(443–471). Retrieved from https://jqst.org/index.php/j/article/view/133.
Abhijeet Bhardwaj, Jay Bhatt, Nagender Yadav, Om Goel, Dr. S P Singh, Aman Shrivastav. Integrating SAP BPC with BI Solutions for Streamlined Corporate Financial Planning. Iconic Research And Engineering Journals, Volume 8, Issue 4, 2024, Pages 583-606.
Pradeep Jeyachandran, Narrain Prithvi Dharuman, Suraj Dharmapuram, Dr. Sanjouli Kaushik, Prof. (Dr.) Sangeet Vashishtha, Raghav Agarwal. Developing Bias Assessment Frameworks for Fairness in Machine Learning Models. Iconic Research And Engineering Journals, Volume 8, Issue 4, 2024, Pages 607-640.
Bhatt, Jay, Narrain Prithvi Dharuman, Suraj Dharmapuram, Sanjouli Kaushik, Sangeet Vashishtha, and Raghav Agarwal. (2024). Enhancing Laboratory Efficiency: Implementing Custom Image Analysis Tools for Streamlined Pathology Workflows. Integrated Journal for Research in Arts and Humanities, 4(6), 95–121. https://doi.org/10.55544/ijrah.4.6.11
Jeyachandran, Pradeep, Antony Satya Vivek Vardhan Akisetty, Prakash Subramani, Om Goel, S. P. Singh, and Aman Shrivastav. (2024). Leveraging Machine Learning for Real-Time Fraud Detection in Digital Payments. Integrated Journal for Research in Arts and Humanities, 4(6), 70–94. https://doi.org/10.55544/ijrah.4.6.10
Pradeep Jeyachandran, Abhijeet Bhardwaj, Jay Bhatt, Om Goel, Prof. (Dr.) Punit Goel, Prof. (Dr.) Arpit Jain. (2024). Reducing Customer Reject Rates through Policy Optimization in Fraud Prevention. International Journal of Research Radicals in Multidisciplinary Fields, 3(2), 386–410. https://www.researchradicals.com/index.php/rr/article/view/135
Pradeep Jeyachandran, Sneha Aravind, Mahaveer Siddagoni Bikshapathi, Prof. (Dr.) MSR Prasad, Shalu Jain, Prof. (Dr.) Punit Goel. (2024). Implementing AI-Driven Strategies for First- and Third-Party Fraud Mitigation. International Journal of Multidisciplinary Innovation and Research Methodology, 3(3), 447–475. https://ijmirm.com/index.php/ijmirm/article/view/146
Jeyachandran, Pradeep, Rohan Viswanatha Prasad, Rajkumar Kyadasu, Om Goel, Arpit Jain, and Sangeet Vashishtha. (2024). A Comparative Analysis of Fraud Prevention Techniques in E-Commerce Platforms. International Journal of Research in Modern Engineering and Emerging Technology (IJRMEET), 12(11), 20. http://www.ijrmeet.org
Jeyachandran, P., Bhat, S. R., Mane, H. R., Pandey, D. P., Singh, D. S. P., & Goel, P. (2024). Balancing Fraud Risk Management with Customer Experience in Financial Services. Journal of Quantum Science and Technology (JQST), 1(4), Nov(345–369). https://jqst.org/index.php/j/article/view/125
Jeyachandran, P., Abdul, R., Satya, S. S., Singh, N., Goel, O., & Chhapola, K. (2024). Automated Chargeback Management: Increasing Win Rates with Machine Learning. Stallion Journal for Multidisciplinary Associated Research Studies, 3(6), 65–91. https://doi.org/10.55544/sjmars.3.6.4