Embedded Graph-Vector Database for AI Applications

Documentation · Issues · Contact

---

SensibleDB, by Sensible Analytics, is a unified database that makes it easy to build all the components needed for an AI application in a single platform.

You no longer need a separate application DB, vector DB, graph DB, or application layers to manage multiple storage locations. SensibleDB combines graph, vector, and embedded storage into one lightweight engine — like SQLite for knowledge graphs.

SensibleDB Explorer

A beautiful, interactive UI for exploring your graph data visually.

---

Key Features

Built-in MCP tools	SensibleDB has built-in MCP support to allow your agents to discover data and walk the graph rather than generating human readable queries.
Built-in Embeddings	No need to embed your data before sending it to SensibleDB, just use the Embed function to vectorize text.
Tooling for RAG	SensibleDB has a built-in vector search, keyword search, and graph traversals that can be used to power any type of RAG applications.
Secure by Default	SensibleDB is private by default. You can only access your data through your compiled SensibleQL queries.
Ultra-Low Latency	SensibleDB is built in Rust and uses LMDB as its storage engine to provide extremely low latencies.
Type-Safe Queries	SensibleQL is 100% type-safe, which lets you develop and deploy with the confidence that your queries will execute in production
Embedded Mode	Use SensibleDB as a lightweight embedded database in your Rust applications with zero external dependencies.
Visual Explorer	Interactive graph visualization, natural language chat, and automated report generation via the SensibleDB Explorer UI.

Embedded Mode

SensibleDB can be used as an embedded database in Rust applications. Enable with the embedded feature:

[dependencies]
sensibledb-db = { version = "1.3", features = ["embedded"] }

Quick Start (Embedded)

use sensibledb_db::embedded::{Database, Node};

let db = Database::open("./my_db")?;
let mut tx = db.write_transaction()?;

tx.put_node(Node {
    id: 1,
    label: "User".into(),
})?;

tx.commit()?;

Embedded Features

• Storage: In-memory storage with optional persistence
• Graph: Node/edge CRUD with transactions
• Vector: Cosine similarity search
• Traversal: BFS/DFS graph traversal
• Indices: Secondary indices for fast lookups

Getting Started

SensibleDB CLI

Start by installing the SensibleDB CLI tool to deploy SensibleDB locally.

1. Install CLI

   curl -sSL "https://install.sensibledb-db.com" | bash

2. Initialize a project

   mkdir <path-to-project> && cd <path-to-project>
   sensibledb init

3. Write queries

   Open your newly created .hx files and start writing your schema and queries. Head over to our docs for more information about writing queries.

   N::User {
      INDEX name: String,
      age: U32
   }
   
   QUERY getUser(user_name: String) =>
      user <- N<User>({name: user_name})
      RETURN user

4. (Optional) Check your queries compile

   sensibledb check

5. Deploy your queries to their API endpoints

   sensibledb push dev

6. Start calling them using our TypeScript SDK or Python SDK. For example:

   import SensibleDB from "sensible-ts";
   
   // Create a new SensibleDB client
   // The default port is 6969
   const client = new SensibleDB();
   
   // Query the database
   await client.query("addUser", {
     name: "John",
     age: 20,
   });
   
   // Get the created user
   const user = await client.query("getUser", {
     user_name: "John",
   });
   
   console.log(user);

Project Structure

SensibleDB/
├── sensibledb-db/          # Core database engine (Rust)
├── sensibledb-cli/         # Command-line interface
├── sensibledb-explorer/    # Visual graph explorer UI (Tauri + SolidJS)
├── sensibledb-container/   # Docker container deployment
├── sensibledb-macros/      # Procedural macros for SensibleQL
├── metrics/                # Telemetry and metrics
├── sensibleql-tests/              # Query language test suite
├── e2e/                    # Playwright E2E tests (65 tests)
└── docs/                   # Documentation source

Documentation

Full documentation is available at https://sensible-analytics.github.io/SensibleDB/

• Getting Started
• SensibleQL Query Language
• SDKs
• Architecture

License

SensibleDB is licensed under the AGPL (Affero General Public License).

Commercial Support

SensibleDB is available as a managed service for selected users. If you're interested in using SensibleDB's managed service or want enterprise support, contact us for more information and deployment options.

---

Sensible Analytics — Making AI applications simpler with unified data storage.

Contributors