✦༺✧ GraVexDB ✧༻✦

Welcome to my high-performance, in-memory graph database project! This project was developed as a learning experience to gain a deeper understanding of graph databases and optimize their performance using C++. The goal was to create an efficient and fast graph database that can handle large-scale data and complex queries.

✧ Features

In-Memory Storage: The graph database is designed to store all data in memory, providing lightning-fast access and eliminating the need for disk I/O operations.
High Performance: Leveraging the power of C++, the database is optimized for speed and efficiency, allowing for quick traversal and querying of large graphs.
Flexible Graph Structure: The database supports a flexible graph structure, allowing nodes and edges to have arbitrary properties and attributes.
Efficient Algorithms: Implements efficient algorithms for common graph operations, such as breadth-first search (BFS), depth-first search (DFS), and shortest path finding.
Thread-Safe: The database is designed to be thread-safe, enabling concurrent access and modifications from multiple threads.
Serialization: Provides functionality to serialize and deserialize the graph data, allowing for persistent storage and retrieval.

✧ Getting Started

To get started with the graph database, follow these steps:

Clone the repository:

git clone https://github.com/your-username/graph-database.git

Navigate to the project directory:
```
cd graph-database
```
Build the project using CMake:
```
mkdir build
cd build
cmake ..
make
```
Run the tests to ensure everything is working correctly:
```
ctest
```
You can now use the graph database in your own projects by linking against the graph_db library.

✧ Usage

Here's a simple example of how to use the graph database:

#include "graph.h"
#include "graph_traversal.h"
#include "graph_query.h"
#include <iostream>

int main() {
    auto graph = std::make_shared<Graph>();

    // Adding nodes
    graph->addNode(1);
    graph->addNode(2);
    graph->addNode(3);

    // Adding edges
    graph->addEdge(1, 2, 1);
    graph->addEdge(1, 3, 1);
    graph->addEdge(2, 3, 1);

    // Performing BFS traversal
    auto bfsResult = GraphTraversal::BFS(graph, 1);
    std::cout << "BFS Traversal: ";
    for (const auto& node : bfsResult) {
        std::cout << node->getId() << " ";
    }
    std::cout << std::endl;

    // Performing shortest path query
    auto shortestPath = GraphQuery::getShortestPath(graph, 1, 3);
    std::cout << "Shortest Path: ";
    for (const auto& node : shortestPath) {
        std::cout << node->getId() << " ";
    }
    std::cout << std::endl;

    return 0;
}

✧ Benchmarks

The project includes benchmark tests to measure the performance of various graph operations. To run the benchmarks, use the following commands:

./graph_benchmark
./traversal_benchmark

The benchmark results will be displayed in the console, showing the execution time for each operation.

✧ Future Enhancements

Here are some planned enhancements and features for the graph database:

Support for persistent storage using disk-based indexes
Implement more advanced graph algorithms, such as PageRank and community detection
Optimize memory usage and reduce memory fragmentation
Enhance query capabilities with support for complex graph patterns and regular expressions
Develop a Python binding for easy integration with other projects

✧ License

This project is licensed under the MIT License.