# Project Proposal: Enhancing Graph Storage in JSON Format

## Introduction

In our current system, we can use the COPY function in PostgreSQL to save graphs in a tabular format. However, this approach falls short when dealing with complex graphs, as graphs are inherently more intricate structures than tabular data. To address this limitation and improve our graph storage capabilities, we propose a project aimed at studying the feasibility of saving graphs in JSON format. This project will involve designing the necessary requirements, establishing milestones, implementing the functionality, and rigorously testing the code.

## Tasks

The primary tasks of this project are as follows:

1. **Feasibility Study**: Conduct a thorough feasibility study to analyze the technical, performance, and practical aspects of storing graphs using JSON format.

2. **Requirement Design**: Define the requirements for saving graphs in JSON format. This includes identifying the modern day in-use JSON schema of the graph representation, chosing and modifying one data model ensuring compatibility with existing data models, and determining the optimal way to map graph properties to JSON attributes.

3. **Milestone Definition**: Divide the project into well-defined milestones, each representing a crucial phase of development, from requirement gathering to testing and deployment.

4. **Implementation**: Develop the necessary codebase to enable the storage of graphs in JSON format. This includes creating functions and procedures to handle the transformation of graph data into JSON and integrating this functionality into the existing system's infrastructure.

5. **Testing and Validation**: Rigorously test the newly implemented code to ensure its reliability, performance, and correctness. This involves both unit testing and integration testing with various types of graphs, including simple and complex cases.

## Methodology

1. **Feasibility Study**: In this phase, the team will assess the advantages and challenges of adopting JSON as the storage format for graphs. Performance benchmarks will be carried out to gauge the efficiency of querying and retrieving graph data in JSON format. The study will also explore the impact on storage requirements and data integrity.

2. **Requirement Design**: Based on the findings of the feasibility study, the team will design the requirements for the JSON graph storage feature. This includes defining the JSON schema for representing graph nodes, edges, attributes, and metadata.

3. **Milestone Definition**: The project will be divided into milestones as follows:
- Milestone 1: Feasibility study completion and requirement design.
- Milestone 2: Core implementation of JSON graph storage functionality.
- Milestone 3: Testing and refinement of the implementation.
- Milestone 4: Integration of the JSON storage feature into the AGE.
- Milestone 5: Final testing, documentation, and deployment preparation.

4. **Implementation**: The team will develop functions that convert graph data into JSON format and vice versa. Error handling, validation, and optimizations for performance will be incorporated during implementation.

5. **Testing and Validation**: Comprehensive testing will be carried out to ensure that the JSON graph storage functionality meets the required standards. This includes verifying data consistency, assessing performance benchmarks, and identifying potential edge cases.

## Deliverables

1. Feasibility study report detailing the findings and recommendations.
2. Requirements specification document outlining the JSON graph storage structure and integration guidelines.
3. Implementation of the JSON graph storage functionality, fully integrated with the existing system.
4. Test suite containing unit tests and integration tests to ensure the functionality's correctness and performance.
5. Documentation for the implemented feature, including usage instructions and best practices.

## Conclusion

By augmenting our graph storage capabilities through JSON formatting, our goal is to transcend the constraints of tabular storage and offer a streamlined and intuitive method for representing intricate graphs. This endeavor not only enhances the cohesion of the AGE ecosystem but also primes us to seamlessly integrate with diverse graph-oriented systems. This structured approach encompasses feasibility assessment, requirement design, implementation, and testing, ensuring a comprehensive and successful project outcome.