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Blockchain-Enabled Large-Scale Transaction Management

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  • © 2026

Overview

  • Explores critical transaction processing issues focusing on confidentiality, verifiability, scalability and performance
  • Presents techniques that facilitate development of efficient data management systems using blockchain
  • Explains how permissioned blockchains enable effective processing of transactions in large-scale data management systems

Part of the book series: Synthesis Lectures on Data Management (SLDM)

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About this book

This book offers a thorough overview of permissioned blockchain systems, emphasizing how they can tackle key challenges in large-scale transaction management systems. Modern transaction systems operate in untrustworthy environments where numerous distrustful entities interact while maintaining data on untrusted infrastructure. By relying on Byzantine fault-tolerant protocols, permissioned blockchain systems have enabled a large class of distributed applications. The presentation focuses on four critical requirements: performance, scalability, confidentiality, and verifiability, which are crucial for effective blockchain operations. Throughout the book, various techniques are explored to address these requirements. The goal is to enhance understanding of the fundamental issues in transaction processing and present techniques that facilitate efficient large-scale transaction management system development in untrusted environments. The practicality of these techniques is highlighted through real-world applications.

Keywords

Table of contents (8 chapters)

Authors and Affiliations

  • Department of Computer Science, Stony Brook University, Stony Brook, USA

    Mohammad Javad Amiri

  • Department of Computer Science, University of California, Santa Barbara, Santa Barbara, USA

    Divyakant Agrawal

  • Department of Computer Science, UUniversity of California, Santa Barbara, Santa Barbara, USA

    Amr El Abbadi

About the authors

Mohammad Javad Amiri is an Assistant Professor in the Department of Computer Science at Stony Brook University. Before joining Stony Brook, he was a postdoctoral researcher in the Computer and Information Science department at the University of Pennsylvania. He received his Ph.D. in Computer Science at the University of California, Santa Barbara. His research mainly lies at the intersection of data management and distributed systems, focusing on distributed transaction processing, consensus protocols, and blockchains.


Divyakant Agrawal is a Distinguished Professor of Computer Science at the University of California, Santa Barbara. Over the course of his career, he has published more than 400 research articles and has mentored approximately 50 Ph.D. students. He serves as Editor-in-Chief of the Springer journal on Distributed and Parallel Databases and has either served or is serving on several Editorial Boards, including for ACM Transactions on Databases, IEEE Transactions on Data and Knowledge Engineering, ACM Transactions on Spatial Algorithms and Systems, ACM Books, and The VLDB Journal. He is currently serving as the Chair of ACM Special Interest Group on Management of Data (SIGMOD). He is a Fellow of the ACM, the IEEE, and the AAAS.

 

Amr El Abbadi is a Distinguished Professor of Computer Science at the University of California, Santa Barbara. Professor El Abbadi is an ACM Fellow, AAAS Fellow, and IEEE Fellow. He has served as a journal editor for several database journals and has been Program Chair for multiple databases and distributed systems conferences. He has published over 400 articles on databases and distributed systems and has supervised more than 40 Ph.D.

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