This article examines modern database indexing methods and proposes new approaches to their optimization to improve data access speed and reduce storage and maintenance costs. Structures such as B-Tree and Hash indexes, as well as hardware-specific and hybrid methods adapted to large data volumes and workloads, are analyzed. Based on a theoretical analysis and a review of empirical research, recommendations are developed for selecting and combining index structures for various scenarios: transactional systems, big data warehouses, and machine learning systems. The obtained results significantly reduce retrieval time, improve scalability, and reduce index update overhead, making the proposed approaches relevant for modern distributed and highly loaded data storage systems.

Data indexing, B-Tree, Hash index

"Indexing in Databases — DBMS" — an overview of indexing, B-Tree/Hash data structures, their features, and applications.

"Understanding B-Tree and Hash Indexing in Databases" — a comparative analysis of B-Tree and Hash indexes, their advantages and limitations.

"A Case Study on B-Tree Database Indexing Technique" — an empirical study of the effectiveness of B-Tree indexes on specific DBMSs.

"Indexing techniques and structured queries for relational database management systems" — a study of the application of various indexing methods in relational databases.

"Revisiting Database Indexing for Parallel and Accelerated Hardware" — a modern study of hardware-specific indexes optimized for modern CPU/GPU architectures.

“How Database Indexing Techniques Impact AI Workloads” – an analysis of the impact of indexing methods on the efficiency of AI pipelines and machine learning systems.

Shamsiddin Yuldashev, Baxtiyor Abdullayev. “Eng kuchli shifrlash algoritmlari : zamonaviy xavfsizlikning asosiy tayanchi”, TerDU xabarlari 2025-yil 17-oktabr, 2-tom. https://journals.tersu.uz/index.php/1/article/view/48

Saidakhon Atajonova Bakhtiyor Abdullayev “Increasing information and communicative competencies among teachers of technical universities “, 2024 –year 27-november, AIP Conference Proceedings.