Mini Distributed Database Engine

This paper presents the design and implementation of a Distributed Database System aimed at efficient data storage, processing, and retrieval across multiple nodes. The system uses a client–coordinator– worker architecture, where queries are received by the coordinator and routed to appropriate worker nodes using hash-based partitioning. It supports operations such as data insertion, selection, and distributed query execution. Replication is implemented to ensure data availability, while a fault tolerance mechanism allows the system to continue operation even if a node fails. The coordinator aggregates results from multiple workers, removes duplicates, and returns a consistent output to the client. Experimental results show that the system performs efficiently with improved scalability, reliability, and performance, making it suitable for distributed data management applications.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-26
DOI
https://doi.org/10.5281/zenodo.20915960
Primary Topic
Advanced Database Systems and Queries
Type
article
Field-Weighted Citation Impact
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article

Mini Distributed Database Engine

Dr. A. Ratna Raju, Dr. K. Mahesh Kumar, Theetla Prajwal, Vardhanapu Samuel Abhishek
Zenodo (CERN European Organization for Nuclear Research)
Advanced Database Systems and Queries
article

Mini Distributed Database Engine

Dr. A. Ratna Raju, Dr. K. Mahesh Kumar, Theetla Prajwal, Vardhanapu Samuel Abhishek
article en

Abstract

This paper presents the design and implementation of a Distributed Database System aimed at efficient data storage, processing, and retrieval across multiple nodes. The system uses a client–coordinator– worker architecture, where queries are received by the coordinator and routed to appropriate worker nodes using hash-based partitioning. It supports operations such as data insertion, selection, and distributed query execution. Replication is implemented to ensure data availability, while a fault tolerance mechanism allows the system to continue operation even if a node fails. The coordinator aggregates results from multiple workers, removes duplicates, and returns a consistent output to the client. Experimental results show that the system performs efficiently with improved scalability, reliability, and performance, making it suitable for distributed data management applications.

Zenodo (CERN European Organization for Nuclear Research)
Decent work and economic growth
Openalex Percentile: Top 4%
Advanced Database Systems and Queries
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