Creating a database with a repository is a very strategic approach, especially if the goal is to ensure data consistency and integrity.
A repository is essentially a “single source of truth” for all critical business data. It allows data to be centralized and normalized so that it is consistent and accessible by all systems and applications.
Here are some steps and key points for defining a database with a repository:
Needs Analysis: Understand the business needs and the types of data that will be stored. Identify the relationships between these data.
Database Schema Design: Draw a data model that represents the structure of your database. This includes defining tables, fields, primary keys, and foreign keys.
Data Normalization: Organize data to reduce redundancy and improve data integrity. Data should be divided into logical entities.
Repository Definition: Create the repository as a central entity in your database. This includes managing metadata, data validation rules, and update policies.
Implementation of Consistency Controls: Add constraints and integrity rules (such as referential integrity constraints) to ensure that data remains consistent.
Security and Access: Implement security mechanisms to protect sensitive data and define appropriate access levels for users.
Testing and Validation: Test the database to ensure it meets requirements and functions correctly. Include load and performance tests to ensure it can handle the expected data volumes.
Documentation: Write comprehensive documentation on the database structure, data management rules, and usage procedures.
By using Zig to develop this suite of programs, you will benefit from a language that favors security and performance.
If you have specific questions or need concrete examples for some of these steps, feel free to ask.
Your project has every chance of success with good planning and rigorous execution
That’s why I created a terminal-based designer, TERMCURS, which can be found on GitHub. It allows me to define my input and visualization screens where fields manage data consistency. Then, I redefined the ZFIELD mode, which allows me to have finer control over a field corresponding to a standard found on mainframes like the AS/400, as well as ZDCML, which allows me to handle numeric zones with 38 digits or more. With this, I can tackle creating a repository.
As an additional note, I chose the Zig language because it seemed coherent and free of ambiguities. Although it is not yet in version 1, it already has a very advanced approach. A standout feature is its referential integrity control, which I value highly coming from the IBM mainframe world.
Of course, it could use more usual documentation, but we have direct access to its composition through its language documentation, and it has a very active community. Sometimes I have to search for how to write certain things because I come from an IBM world where everything has already been thought out. Fortunately, I have been working with C since 1995 and have extensive experience in my field on IBM.
