Implementing a Data Vault 2.0 Model on the Quorum Blockchain [Part 1]

In a world where data management is becoming crucial for businesses, technological innovation constantly pushes the boundaries. Among the promising advancements, Blockchain and Data Vault 2.0 stand out. They are redefining traditional paradigms of data warehousing and security.

Blockchain, with its decentralized and immutable structure, offers unprecedented transparency and security. On the other hand, Data Vault 2.0 provides a robust methodology for data modeling, allowing for increased flexibility and scalability. However, integrating these two technologies, while potentially revolutionary, presents unique challenges.

This series of articles delves deeply into the possible synergies between Blockchain and Data Vault 2.0. It highlights the inherent complexities of their joint implementation. The series is structured into several parts, addressing technical issues, security and performance considerations, and exploring the innovation opportunities offered by this technological convergence. Each part focuses on a specific aspect of this integration, allowing for a comprehensive and nuanced understanding of the challenges and potential solutions.

Prepare to dive into a universe where data management meets cutting-edge technology, paving the way for new possibilities in the future of information.

We use private and permissioned blockchains in this article series.

Implementing a data warehouse for a business on a public Blockchain does not make sense. It is important to clarify this to avoid any confusion.

Introduction to Data Vault 2.0

The Data Vault 2.0 methodology is a modern approach to data modeling, aimed at addressing the challenges of complex data environments. This method is suited to constantly evolving contexts.

Introduction to Private and Permissioned Blockchain

Private and permissioned Blockchain technology is a variant of blockchain designed for environments where confidentiality is paramount. Access control and efficiency are also priorities in these contexts.

Here is a summary of the advantages and objectives of this technology:

Objectives and Advantages of Private and Permissioned Blockchains:

1. Confidentiality: Ensuring that only authorized parties access data and transactions, crucial for companies handling sensitive information.
2. Access Control: Allowing organizations to define and manage network participants, determining what actions each participant is authorized to perform.
3. Efficiency: Optimizing network performance to be faster and less costly than public blockchains.
4. Regulatory Compliance: Facilitating adherence to data protection and security regulations by implementing strict access controls and ensuring complete traceability.
5. Inter-company Collaboration: Encouraging collaboration between multiple organizations by offering a secure and transparent platform for data sharing and transaction management.

In summary, private and permissioned blockchain not only offers a secure solution but also an efficient and customizable one.

It is ideal for businesses that can leverage blockchain technology while maintaining control over data access and ensuring information confidentiality.

Smart Contract

Smart contracts are self-executing agreements with terms directly coded. They operate on decentralized platforms such as Quorum or Ethereum, primarily using the Solidity language for their development.

Key Elements of Smart Contracts:

• State Variables: Data recorded on the blockchain.
• Functions: Logic to modify the state.
• Events: Logs to track off-chain actions.

Implementing the Data Vault Model on Blockchain

Let’s explore how to create the entities of a Data Vault 2.0 model in a smart contract developed in Solidity. To illustrate our explanations, we rely on the example of the “demodb-bookings” database: https://postgrespro.com/docs/postgrespro/12/demodb-bookings

We use the model from the following article: “Practical Introduction to Data Vault Modeling.” The associated repository is available here: https://github.com/nshcode/data-vault-modeling/tree/main.

Taking the entity-relationship model for seat management in airplanes:

How to create DataVault entities (Hub, Sat, and Link) in a smart contract:

The Aircraft and Seat Hubs:

    struct h_aircraft {
        bytes32 hk_aircraft;
        string aircraft_code;
        uint256 load_date_ts;
        string record_source;
    }

    struct h_seat{
        bytes32 hk_seat;
        string aircraft_code;
        string seat_no;
        uint256 load_date_ts;
        string record_source;
    }

The link between entities:

    struct l_aircraft_seat{
        bytes32 lhk_aircraft_seat;
        bytes32 hk_aircraft;
        bytes32 hk_seat;
        uint256 load_date_ts;
        string record_source;
    }

The satellites: where descriptive data is located:

    struct s_seat{
        bytes32 hk_seat;
        uint256 load_date_ts;
        string fare_conditions;
        string record_source;
    }

    struct s_aircraft{
        bytes32 hk_aircraft;
        uint256 load_date_ts;
        string model;
        uint range;
        string record_source;
    }

We now have the necessary data structures. To store these entities, it is necessary to create collections:

    mapping (bytes32 => h_aircraft) map_h_aircrafts;
    bytes32[] _h_aircrafts;

    mapping (bytes32 => h_seat) map_h_seats;
    bytes32[] _h_seats;

    mapping (bytes32 => l_aircraft_seat) map_l_aircraft_seats;
    bytes32[] _l_aircraft_seat;

    mapping (bytes32 => s_aircraft) map_s_aircrafts;
    bytes32[] _s_aircrafts;

    mapping (bytes32 => s_seat) map_s_seats;
    bytes32[] _s_seats;

Here, it is important to explain the collections:

First, we define a mapping-type collection.

    mapping (bytes32 => h_aircraft) map_h_aircrafts;

A mapping in Solidity is a data structure that functions like a lookup table.
Mappings offer quick access to data via unique keys but do not allow iteration over keys or knowing their number. Arrays, on the other hand, allow storing ordered collections and easy iteration but can be costly for add or remove operations.

Associating an array for keys with a mapping is important because it allows benefiting from the quick access of the mapping while retaining the ability to iterate over keys through the array, thus optimizing data management.

    bytes32[] _h_aircrafts;

In our next article, we will see how to populate the blockchain using functions.