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A Survey on the Integration of Blockchains and Databases
Changhao Zhu1, Junzhe Li1, Ziyue Zhong1
1Beijing Institute of Technology, Beijing, China.
Blockchain and database fusion systems offer enhanced security, efficiency, and privacy for data management. This survey explores these integrated systems, their classifications, and future directions in the field.
Area of Science:
- Computer Science
- Data Management
- Blockchain Technology
Background:
- Blockchain's success in cryptocurrencies highlights its potential for data management.
- A growing trend integrates blockchains with traditional databases for improved security, efficiency, and privacy.
- Existing research lacks a clear taxonomy for blockchain-database fusion systems.
Purpose of the Study:
- To survey and classify existing blockchain-related data management technologies.
- To analyze three types of fusion systems, their design spaces, and trade-offs.
- To provide insights into current solutions and identify future research directions.
Main Methods:
- Classification of blockchain-data management technologies based on their position in the blockchain-database spectrum.
- Analysis of three distinct types of fusion systems.
- Comparative study of typical systems, techniques, and solutions within each fusion model.
Main Results:
- A taxonomy categorizing blockchain-data management systems is proposed.
- Detailed analysis of three fusion system types, revealing their respective design spaces and trade-offs.
- Comparative insights into various fusion models and their practical applications.
Conclusions:
- Fusion systems combining blockchains and databases are crucial for future data management.
- Understanding the advantages and limitations of these systems is vital for academia and industry.
- Further research is needed to address unsolved challenges and explore promising directions in integrated systems.
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