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It empowers developers, researchers, and healthcare professionals to build, query, and analyze interconnected medical data with high context-awareness. By leveraging a graph-native approach, GraphDB unlocks insights from complex relationships that traditional relational databases struggle to handle, making it an ideal complement to existing Electronic Health Record (EHR) systems.\n\n\u003e **Note**: GraphDB is under active development. APIs and behavior may change before the 1.0 release. In production, ensure encryption, authentication, and access controls are configured to meet HIPAA/GDPR compliance requirements.\n\n## 📁 Table of Contents\n\n* [🚑 Why Medical Practices Need GraphDB](#-why-medical-practices-need-graphdb)\n* [🧠 Key Benefits](#-key-benefits)\n* [🧹 What It Does](#-what-it-does)\n* [🧹 Quick Example](#-quick-example)\n* [🧹 Architecture](#-architecture)\n* [🔌 How It Works](#-how-it-works)\n* [🌐 Complementing Existing EHRs](#-complementing-existing-ehrs)\n* [🧪 Example Use Cases](#-example-use-cases)\n* [🚀 Getting Started](#-getting-started)\n  * [📋 Installation Prerequisites](#-installation-prerequisites)\n  * [🛠️ Building GraphDB](#-building-graphdb)\n  * [🚀 Running GraphDB Components](#-running-graphdb-components)\n* [📂 File Structure](#-file-structure)\n* [📦 Crate/Module Details](#-cratemodule-details)\n* [⚡ Ports, Daemons, and Clusters](#-ports-daemons-and-clusters)\n* [💻 Command-Line Interface (CLI) Usage](#-command-line-interface-cli-usage)\n* [🌐 REST API Usage](#-rest-api-usage)\n* [🗄️ Storage Backends](#-storage-backends)\n* [🔮 Future Vision: Advanced Querying \u0026 AI Integration](#-future-vision-advanced-querying--ai-integration)\n* [🧬 Medical Ontology Support](#-medical-ontology-support)\n* [📢 Contributing](#-contributing)\n* [📜 License](#-license)\n* [🌐 Links](#-links)\n\n## 🚑 Why Medical Practices Need GraphDB\n\nElectronic Health Record (EHR) systems typically rely on linear, table-based relational models. However, medical data is inherently interconnected, forming complex relationships that are challenging to represent or query efficiently in traditional systems. For example:\n\n* Patients have encounters with providers 👩‍⚕️.\n* Encounters generate diagnoses, procedures, notes, and billing codes 📝.\n* Medications and prescriptions involve drug interactions and side effects 💊.\n* Data flows from devices, labs, insurers, pharmacies, and public health databases 📊.\n\nComplex queries, such as:\n* \"Which patients are at risk based on recent prescriptions and lab results?\" ⚠️\n* \"Which providers might be undercoding based on their encounter history?\" 📉\n* \"Show a patient’s medical, behavioral, and socioeconomic history over the past 3 years.\" 📈\n\nare inefficient or infeasible in relational models. GraphDB addresses this gap by providing a graph-native database that excels at modeling and querying these relationships, enabling faster, more intuitive insights for healthcare applications.\n\n## 🧠 Key Benefits\n\nGraphDB offers unique advantages for healthcare data management:\n* **Intuitive Data Modeling**: Represents complex medical relationships (e.g., patient-provider interactions, drug interactions) as nodes and edges, making data exploration natural and efficient.\n* **Powerful Querying**: Supports natural language, Cypher, SQL, and GraphQL queries, enabling both technical and non-technical users to extract insights.\n* **Seamless Integration**: Complements existing EHR systems by ingesting data in formats like FHIR, HL7, or CSV, acting as a smart middleware layer.\n* **Scalable Architecture**: Supports standalone, daemonized, or clustered deployments for flexibility and performance.\n* **Healthcare-Specific Features**: Includes built-in support for medical ontologies (e.g., ICD-10, SNOMED) and planned AI-driven analytics for advanced insights.\n* **Open-Source and Extensible**: MIT-licensed with a pluggable architecture, encouraging community contributions and custom extensions.\n\n## 🧹 What It Does\n\nGraphDB is designed to handle the complexity of medical data through:\n* **Graph-Native Data Model**: Uses vertices (nodes) and edges (relationships) to capture nuanced connections in medical data, such as patient diagnoses or provider interactions.\n* **Natural Language Querying**: Transforms high-level or natural language queries into efficient graph query languages (e.g., Cypher, SQL, GraphQL) for ease of use.\n* **Flexible Deployment**: Offers a powerful CLI for interactive and scripted use, alongside a daemonized REST API for integration with existing systems.\n* **Pluggable Extensions**: Supports healthcare-specific plugins for standards like FHIR, HL7, ICD-10, CPT, and X12.\n* **Middleware Capabilities**: Acts as a context-aware layer for legacy or modern EHR systems, enhancing their relational capabilities.\n* **Advanced Analytics**: Enables graph analytics, risk modeling, explainable AI, and auditable traceability for compliance and insights.\n\n## 🧹 Quick Example\n\nHere’s a simple Cypher query to find patients diagnosed with Type 2 Diabetes (ICD-10 code E11):\n\n```cypher\nMATCH (p:Patient)-[:HAS_DIAGNOSIS]-\u003e(d:Diagnosis)\nWHERE d.code = \"E11\"\nRETURN p.name, p.age\n```\n\nThis query traverses the graph to return patient names and ages, demonstrating GraphDB’s ability to handle relational queries efficiently.\n\n## 🧹 Architecture\n\nGraphDB’s modular, daemonized architecture ensures scalability, performance, and flexibility. Below is a visual representation of its components and their interactions:\n\n```\n+-------------------------------------------------------------------------+\n|                  graphdb-cli (Interactive \u0026 Scriptable Client)          |\n| +---------------------------------------------------------------------+ |\n| | Parses CLI commands, transforms queries, dispatches to daemons      | |\n| +---------------------------------------------------------------------+ |\n+------------------------------------|------------------------------------+\n                                     | (Local Process / HTTP / gRPC)\n                                     ↓\n+-------------------------------------------------------------------------+\n|                  graphdb-rest_api (REST API Gateway)                    |\n| +---------------------------------------------------------------------+ |\n| | Exposes RESTful endpoints for programmatic access                  | |\n| | Handles authentication, routing, and data serialization             | |\n| +---------------------------------------------------------------------+ |\n+------------------------------------|------------------------------------+\n                                     | (gRPC / Internal IPC)\n                                     ↓\n+-------------------------------------------------------------------------+\n|                  graphdb-daemon (Core Graph Processing Daemon)          |\n| +---------------------------------------------------------------------+ |\n| | Manages graph state, executes queries, handles concurrency          | |\n| | Uses graphdb-lib for graph modeling and query execution            | |\n| | Supports single-instance or clustered deployments                  | |\n| +---------------------------------------------------------------------+ |\n+------------------------------------|------------------------------------+\n                                     | (Internal IPC / Storage Protocol)\n                                     ↓\n+-------------------------------------------------------------------------+\n|                  graphdb-storage-daemon (Pluggable Storage Backend)     |\n| +---------------------------------------------------------------------+ |\n| | Manages persistent storage, indexing, and transactional integrity  | |\n| | Supports multiple backends (Postgres, Redis, RocksDB, Sled)         | |\n| +---------------------------------------------------------------------+ |\n```\n\nThis architecture allows independent scaling of components, supporting both lightweight local deployments and distributed, high-performance clusters.\n\n## 🔌 How It Works\n\nGraphDB processes data through a streamlined workflow:\n1. **Input Parsing**: Queries from the CLI or REST API (natural language, Cypher, SQL, or GraphQL) are parsed and transformed into an internal graph traversal representation.\n2. **Daemonized Execution**: The `graphdb-daemon` handles query execution, maintains graph state, and supports concurrent access. It leverages in-memory caching for performance.\n3. **Storage Management**: The `graphdb-storage-daemon` abstracts persistent storage, supporting multiple backends (e.g., Postgres, RocksDB) via pluggable interfaces.\n4. **Integration**: GraphDB can operate standalone for graph analysis or integrate into existing healthcare IT pipelines, enhancing data interoperability.\n\n## 🌐 Complementing Existing EHRs\n\nGraphDB enhances, rather than replaces, existing EHR systems by:\n* **Ingesting Data**: Supports formats like CSV, HL7, FHIR, or direct Postgres connections, making it easy to import data from EHRs.\n* **Transforming Data**: Converts structured and semi-structured data into a queryable graph model, preserving relationships.\n* **Enabling Insights**: Facilitates temporal and semantic joins across disparate datasets, uncovering insights hidden in relational structures (e.g., linking patient records with lab results and billing codes).\n\n## 🧪 Example Use Cases\n\nGraphDB’s graph-native approach unlocks powerful healthcare applications:\n* **Clinical Decision Support**: Identify drug-allergy interactions or suggest treatment paths by traversing patient history graphs in real-time. 🩺\n* **Billing Optimization**: Detect missed CPT coding opportunities or fraudulent billing patterns using graph-based anomaly detection. 💰\n* **Patient Risk Modeling**: Build longitudinal graphs of patient medical, behavioral, and socioeconomic factors for predictive analytics and proactive care. 📊\n* **Security and Compliance**: Visualize user access logs as graphs to ensure HIPAA/GDPR compliance and detect unauthorized access. 🔒\n* **Research and Epidemiology**: Analyze disease propagation networks, identify clinical trial cohorts, or study social determinants of health. 🔬\n\n## 🚀 Getting Started\n\n### 📋 Installation Prerequisites\n\nBefore building GraphDB, ensure the following are installed:\n* **Rust**: Version 1.72 or higher (`rustup install 1.72`).\n* **Cargo**: Included with Rust for building and managing dependencies.\n* **Git**: For cloning the repository.\n* **Optional Backends** (if used):\n  * Postgres: For relational storage.\n  * Redis: For caching.\n  * RocksDB/Sled: For embedded key-value storage.\n\n### 🛠️ Building GraphDB\n\n1. Clone the repository:\n   ```bash\n   git clone [https://github.com/dmitryro/graphdb.git](https://github.com/dmitryro/graphdb.git)\n   cd graphdb\n   ```\n\n2. Build the CLI executable:\n   ```bash\n   cargo build --workspace --release --bin graphdb-cli\n   ```\n\n   The compiled binary will be located at `./target/release/graphdb-cli`.\n\n### 🚀 Running GraphDB Components\n\nGraphDB supports multiple interaction modes:\n* **Interactive CLI**: For exploratory querying and management.\n* **Scripted CLI**: For automation and batch processing.\n* **REST API**: For programmatic integration with other applications.\n\n#### CLI Commands\n* **Start Interactive CLI**:\n  ```bash\n  ./target/release/graphdb-cli --cli\n  ```\n\n  Enter commands like `start`, `stop`, `status`, or `rest graph-query`.\n* **Start a Single Graph Daemon**:\n  ```bash\n  ./target/release/graphdb-cli start --port 9001\n  ```\n\n  Default port is 8080 if `--port` is omitted.\n* **Start a Daemon Cluster**:\n  ```bash\n  ./target/release/graphdb-cli start --cluster 9001-9003\n  ```\n\n  Launches daemons on ports 9001–9003.\n* **Start REST API and Storage Daemon**:\n  ```bash\n  ./target/release/graphdb-cli start --listen-port 8082 --storage-port 8085\n  ```\n\n  REST API runs on port 8082, storage daemon on 8085.\n* **Stop Components**:\n  * Stop all components:\n    ```bash\n    ./target/release/graphdb-cli stop\n    ```\n\n  * Stop specific components:\n    ```bash\n    ./target/release/graphdb-cli stop rest\n    ./target/release/graphdb-cli stop daemon --port 9001\n    ```\n    * Stop the Storage Daemon by port:\n    ```bash\n    ./target/release/graphdb-cli stop storage --port 8085\n    ```\n\n#### Querying Data\n* **Direct CLI Query**:\n  ```bash\n  ./target/release/graphdb-cli --query \"MATCH (n) RETURN n\"\n  ```\n\n* **Interactive CLI Query**:\n  ```\n  graphdb-cli\u003e rest graph-query \"MATCH (p:Patient) RETURN p.name LIMIT 5\"\n  ```\n\n* **REST API Query**:\n  ```bash\n  curl -X POST [http://127.0.0.1:8082/api/v1/query](http://127.0.0.1:8082/api/v1/query) \\\n    -H \"Content-Type: application/json\" \\\n    -d '{\"query\":\"MATCH (n:Person {name: \\\"Alice\\\"}) RETURN n\"}'\n  ```\n\n## 📂 File Structure\n\nThe project is organized for modularity and maintainability:\n* `graphdb-lib/` 🧠: Core graph engine, data structures, and query parsing.\n* `server/` 💻: CLI application (`graphdb-cli`) and its components.\n* `daemon-api/` ⚙️: Interfaces for daemon communication (e.g., gRPC).\n* `rest-api/` 🌐: RESTful API gateway for external access.\n* `storage-daemon-server/` 🗄️: Pluggable storage backend daemon.\n* `proto/` 📦: gRPC service definitions for distributed setups.\n* `models/medical/` ⚕️: Healthcare-specific graph structures and ontologies.\n\n## 📦 Crate/Module Details\n\n### `graphdb-lib` 🧠\n* **Purpose**: Core graph engine with data structures (nodes, edges), traversal algorithms (BFS, DFS, shortest path), and query parsing for Cypher, SQL, and GraphQL.\n* **Features**:\n  * Efficient in-memory graph representation.\n  * Schema management for nodes and relationships.\n  * Query execution engine with support for multiple query languages.\n\n### `server` 💻\n* **Purpose**: Houses the `graphdb-cli` binary for interactive and scripted use.\n* **Subcomponents** (`server/src/cli/`):\n  * `cli.rs`: Parses command-line arguments and dispatches commands.\n  * `commands.rs`: Defines CLI subcommands using the `clap` crate.\n  * `handlers.rs`: Implements logic for commands (e.g., start/stop daemons).\n  * `interactive.rs`: Manages the interactive CLI shell.\n  * `config.rs`: Handles configuration (ports, data directories) via YAML/TOML.\n  * `daemon_management.rs`: Manages daemon lifecycle (spawning, monitoring, stopping).\n  * `help_display.rs`: Generates detailed help messages for CLI commands.\n\n### `daemon-api` ⚙️\n* **Purpose**: Provides programmatic interfaces for controlling `graphdb-daemon` instances.\n* **Features**: Uses gRPC for efficient, language-agnostic communication between components.\n\n### `rest-api` 🌐\n* **Purpose**: Exposes RESTful endpoints for programmatic access.\n* **Key Endpoints**:\n  * `GET /api/v1/health`: Checks system status.\n  * `POST /api/v1/query`: Executes graph queries (Cypher, SQL, GraphQL).\n  * `POST /api/v1/start/port/{port}`: Starts a single daemon.\n  * `POST /api/v1/start/cluster/{start}-{end}`: Starts a daemon cluster.\n  * `POST /api/v1/stop`: Shuts down components (optional parameters for specific daemons).\n  * `POST /api/v1/ingest` (Planned): Ingests data in formats like FHIR.\n  * `GET /api/v1/nodes/{id}` (Planned): Retrieves a specific node.\n  * `GET /api/v1/relationships/{id}` (Planned): Retrieves a specific relationship.\n\n### `storage-daemon-server` 🗄️\n* **Purpose**: Manages persistent storage with a pluggable architecture.\n* **Supported Backends**: Postgres, Redis, RocksDB, Sled.\n* **Features**: Ensures data durability, indexing, and transactional integrity.\n\n### `proto` 📦\n* **Purpose**: Defines gRPC Protobuf messages and services for distributed communication.\n\n### `models/medical` ⚕️\n* **Purpose**: Provides healthcare-specific graph structures and ontologies for context-aware queries.\n\n## ⚡ Ports, Daemons, and Clusters\n\nGraphDB components run as independent daemons, communicating via defined ports:\n\n| Component             | Default Port | Description                              |\n|-----------------------|--------------|------------------------------------------|\n| `graphdb-daemon`      | 8080         | Core graph processing daemon            |\n| `graphdb-rest_api`    | 8082         | REST API gateway                        |\n| `graphdb-storage-daemon` | 8085      | Persistent storage daemon                |\n\n* **Single Instance**: Suitable for local development or small-scale deployments.\n* **Cluster Mode**: Supports distributed processing across multiple ports (e.g., 9001–9003) for scalability.\n* **Use Cases**:\n  * Interactive querying: CLI.\n  * Automation/scripting: REST API.\n  * Batch ingestion: CLI + Daemon.\n  * Distributed processing: gRPC (planned).\n\n## 💻 Command-Line Interface (CLI) Usage\n\nThe `graphdb-cli` binary provides flexible interaction options:\n```bash\n./target/release/graphdb-cli --cli                        # Start interactive shell\n./target/release/graphdb-cli start --port 9001           # Start single daemon\n./target/release/graphdb-cli start --cluster 9001-9003   # Start daemon cluster\n./target/release/graphdb-cli stop                        # Stop all components\n./target/release/graphdb-cli view-graph --graph-id 42    # View graph by ID\n./target/release/graphdb-cli --query \"MATCH (n) RETURN n\" # Execute direct query\n```\n\n## 🌐 REST API Usage\n\nInteract with GraphDB programmatically via the REST API:\n```bash\n# Check system health\ncurl [http://127.0.0.1:8082/api/v1/health](http://127.0.0.1:8082/api/v1/health)\n\n# Execute a graph query\ncurl -X POST [http://127.0.0.1:8082/api/v1/query](http://127.0.0.1:8082/api/v1/query) \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"query\":\"MATCH (n:Person {name: \\\"Alice\\\"}) RETURN n\"}'\n```\n\n## 🗄️ Storage Backends\n\nGraphDB supports pluggable storage backends:\n* **Postgres**: Relational persistence and SQL queries.\n* **Redis**: High-speed caching for transient data.\n* **RocksDB**: Embedded key-value store for local performance.\n* **Sled**: Lock-free, embedded database for Rust.\nCustom backends can be implemented via trait interfaces.\n\n## 🔮 Future Vision: Advanced Querying \u0026 AI Integration\n\nGraphDB aims to evolve into a more intelligent platform:\n* **Natural Language Processing (NLP)**: Enhanced support for conversational queries, enabling non-technical users to interact with the database.\n* **AI-Driven Insights**: Integration with machine learning models for predictive analytics, such as identifying at-risk patients or optimizing clinical workflows.\n* **Graph Visualization**: A planned UI for exploring and visualizing graph data interactively.\n* **Distributed gRPC**: Enhanced support for multi-language, distributed deployments.\n\n## 🧬 Medical Ontology Support\n\nGraphDB supports key healthcare standards:\n* FHIR (STU3/STU4)\n* HL7 (v2/v3)\n* CPT, ICD-10, LOINC, SNOMED\n* X12 (837/835 claims)\n* **Planned**: Retrieval-Augmented Generation (RAG) for NLP queries, time-series support for EEG/EKG data.\n\n## 📢 Contributing\n\nWe welcome contributions to enhance GraphDB:\n* ✅ Cypher query support (complete)\n* [ ] NLP pipeline integration\n* [ ] gRPC enhancements\n* [ ] Graph explorer UI\n\nSubmit pull requests or report issues at [https://github.com/dmitryro/graphdb/issues](https://github.com/dmitryro/graphdb/issues).\n\n## 📜 License\n\nMIT License (see [LICENSE](./LICENSE)).\n\n## 🌐 Links\n\n* **GitHub**: [https://github.com/dmitryro/graphdb](https://github.com/dmitryro/graphdb)\n* **Issues**: [https://github.com/dmitryro/graphdb/issues](https://github.com/dmitryro/graphdb/issues)\n* **Documentation**: [https://docs.rs/graphdb](https://docs.rs/graphdb)\n* **Crates.io**: [https://crates.io/crates/graphdb](https://crates.io/crates/graphdb)\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdmitryro%2Fgraphdb-rs","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdmitryro%2Fgraphdb-rs","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdmitryro%2Fgraphdb-rs/lists"}