Relational database for data storage

Relational database for data storage

Blockchain system and relational database integration:

Method overview: This method integrates blockchain nodes with relational databases (RDBs), allowing clients to use SQL commands to initiate transactions and query transaction data, thereby improving the data query and processing capabilities of blockchain systems.

System architecture: The system architecture includes application layer, extension layer, protocol layer, network layer and storage layer, among which the protocol layer is further divided into network layer and storage layer.

Transaction processing flow:

SQL command processing: The client initiates a transaction instruction containing an SQL write command, the node parses the SQL command, executes a simulated transaction, and checks the block data based on the transaction results.

Block data writing: After the check is successful, the node converts the block data into an SQL write command and writes it to the RDB database.

Example process: It includes steps such as generating SQL query commands to obtain endorsement information, executing simulated transactions, returning simulated transaction results, generating and writing SQL write commands, etc.

Node design and module functions:

Node module: The node includes an endorsement unit, a smart contract unit, a parsing unit, a sorting unit, etc. Each unit is responsible for different functions, such as parsing transaction instructions, executing smart contracts, sorting transactions, etc.

RDB database connection: Nodes interact with the RDB database through smart contracts or direct instructions, execute SQL commands, store and query transaction data.

Double-spending check and data verification:

Double-spending check: By querying the historical transaction information in the RDB database, the node can check whether the transaction is a double-spending transaction to ensure the uniqueness of the transaction.

Data verification: Before generating SQL write commands, the node will verify the block data to ensure the integrity and consistency of the data.

System compatibility and development cost:

Compatibility enhancement: The use of RDB database improves the compatibility of the blockchain system with other systems, making it easier to migrate existing SQL type applications to the blockchain.

Development cost reduction: The interaction between the client and the blockchain system is based on SQL commands, which reduces the difficulty and cost of development.

Specific implementation and application cases:

Fabric system application: The document describes in detail the application of this method in the Hyperledger Fabric system, including the execution of chaincode, storage and query of ledger data, etc.

Other blockchain systems: This method is also applicable to other blockchain systems, and only needs to be adjusted accordingly according to the specific system architecture.

Hardware and software implementation:

Hardware structure: Node devices can be computers, servers or other hardware devices with computing power and network communication capabilities.

Software implementation: The method is implemented through programming and can be integrated into the software of the blockchain node, including the writing of smart contracts, the configuration of database connectors, etc.

These key points comprehensively cover the core content of the document, including the integration of the blockchain system and the RDB database, transaction processing flow, node design and module functions, double-spending checks and data verification, system compatibility and development costs, specific implementation and application cases, and hardware and software implementation.

Short answer questions:

What is the main point?

The main point is to introduce a relational database (RDB) into the blockchain system, and propose a method to use SQL commands to initiate transactions and query transaction data. In this way, the client can directly use SQL commands to interact with the blockchain node, which improves the data query and processing capabilities of the blockchain system.

What is the transaction processing process of the blockchain node?

The transaction processing process of the blockchain node includes: receiving transaction instructions containing SQL write commands initiated by the client, parsing SQL commands, executing simulated transactions, and checking block data based on transaction results. After the check is successful, the node converts the block data into an SQL write command and writes it to the RDB database.

How to enhance the compatibility of the blockchain system?

By introducing a relational database, the blockchain system can be more easily compatible with other systems. The interaction between the client and the blockchain system is based on the widely used SQL language, which reduces the difficulty of migrating existing SQL-type applications to the blockchain, thereby enhancing the compatibility of the blockchain system.

How does the node perform a double-spending check in transaction processing?

When processing a transaction, the node will check whether the transaction is a double-spending transaction by querying the historical transaction information in the RDB database. Specifically, the node can generate an SQL query command to obtain historical information related to the transaction and determine the uniqueness of the transaction based on this information.

What is the role of chaincode in the Fabric system application mentioned in the document?

In the Fabric system application, chaincode is the implementation of smart contracts, responsible for storing and executing smart contract logic. Chaincode can receive transaction instructions, execute corresponding business logic, and update ledger data. Through the execution of chaincode, nodes can complete the simulation, verification, and submission of transactions.

What are the advantages of the proposed solution over traditional blockchain solutions?

The proposed solution has the following advantages over traditional blockchain solutions: improved data query efficiency, because relational databases have stronger data query and analysis capabilities; reduced development difficulty and cost, because the interaction between the client and the blockchain system is based on the widely used SQL language; enhanced system compatibility, making it easier to migrate existing SQL-type applications to the blockchain