# RuVector-WASM: Standalone Vector Database Architecture ## 🎯 Vision **A complete, self-contained vector database with graph and semantic capabilities that runs anywhere - browser, Node.js, Deno, Bun, edge workers - without PostgreSQL.** Think **DuckDB-WASM** but for vector/graph/semantic workloads. --- ## ✨ What You Get ### Complete Feature Set - βœ… **Vector Operations**: All types (f32, f16, binary, sparse), SIMD-optimized distances - βœ… **Graph Database**: Cypher queries, graph traversal, GNN layers - βœ… **Semantic Search**: HNSW indexing, quantization, hybrid search - βœ… **RDF/SPARQL**: W3C-compliant SPARQL 1.1, triple store - βœ… **SQL Interface**: Standard SQL for vector queries - βœ… **Self-Learning**: ReasoningBank, attention mechanisms, adaptive patterns - βœ… **Hyperbolic Embeddings**: PoincarΓ©, Lorentz spaces - βœ… **AI Routing**: Tiny Dancer intelligent routing ### Zero Dependencies - ❌ No PostgreSQL installation - ❌ No Docker required - ❌ No native compilation - βœ… Pure WASM (~5-10MB bundle) - βœ… `npm install @ruvector/wasm` and go! ### Universal Runtime ```bash # Browser # Node.js npm install @ruvector/wasm # Deno import { RuVector } from "https://esm.sh/@ruvector/wasm" # Bun bun add @ruvector/wasm # Cloudflare Workers (edge) import { RuVector } from "@ruvector/wasm" ``` --- ## πŸ—οΈ Architecture ### High-Level Design ``` β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ Query Layer (TypeScript/JavaScript API) β”‚ β”‚ - SQL parser & executor β”‚ β”‚ - Cypher parser & executor β”‚ β”‚ - SPARQL parser & executor β”‚ β”‚ - REST-like API (insert, query, delete) β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ wasm-bindgen β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β–Όβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ RuVector Core (Rust β†’ WASM) β”‚ β”‚ β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ β”‚ β”‚ Storage Engine β”‚ β”‚ β”‚ β”‚ - In-memory tables (DashMap) β”‚ β”‚ β”‚ β”‚ - IndexedDB persistence (browser) β”‚ β”‚ β”‚ β”‚ - OPFS storage (browser) β”‚ β”‚ β”‚ β”‚ - File system (Node.js/Deno/Bun) β”‚ β”‚ β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β”‚ β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ β”‚ β”‚ Index Layer β”‚ β”‚ β”‚ β”‚ - HNSW vector index β”‚ β”‚ β”‚ β”‚ - B-Tree for scalar columns β”‚ β”‚ β”‚ β”‚ - Triple store (SPO, POS, OSP indexes) β”‚ β”‚ β”‚ β”‚ - Graph adjacency lists β”‚ β”‚ β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β”‚ β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ β”‚ β”‚ Execution Engine β”‚ β”‚ β”‚ β”‚ - SQL query planner & executor β”‚ β”‚ β”‚ β”‚ - Cypher graph pattern matching β”‚ β”‚ β”‚ β”‚ - SPARQL triple pattern matching β”‚ β”‚ β”‚ β”‚ - Vector similarity search β”‚ β”‚ β”‚ β”‚ - GNN computation (GCN, GraphSage, GAT) β”‚ β”‚ β”‚ β”‚ - ReasoningBank self-learning β”‚ β”‚ β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β”‚ β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ β”‚ β”‚ SIMD & Optimization β”‚ β”‚ β”‚ β”‚ - WASM SIMD (128-bit) β”‚ β”‚ β”‚ β”‚ - Quantization (binary, scalar, product) β”‚ β”‚ β”‚ β”‚ - Parallel query execution (rayon β†’ WASM threads) β”‚ β”‚ β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ ``` ### Component Breakdown #### 1. Storage Layer (`ruvector-wasm/src/storage/`) **In-Memory Store** (primary): ```rust pub struct Database { tables: DashMap, triple_store: Arc, graph: Arc, indexes: DashMap, } pub struct Table { schema: Schema, rows: RwLock>, vector_columns: HashMap, } ``` **Persistence Adapters**: ```rust trait PersistenceBackend { async fn save(&self, db: &Database) -> Result<()>; async fn load(&self) -> Result; } // Browser: IndexedDB struct IndexedDBBackend; // Browser: OPFS (Origin Private File System) struct OPFSBackend; // Node/Deno/Bun: File system struct FileSystemBackend; ``` #### 2. Query Engines (`ruvector-wasm/src/query/`) **SQL Engine**: ```rust // Reuse existing PostgreSQL SQL functions, but with custom executor pub struct SqlExecutor { parser: SqlParser, planner: QueryPlanner, executor: Executor, } // Example: Vector similarity in SQL // SELECT * FROM docs ORDER BY embedding <=> $1 LIMIT 10 ``` **SPARQL Engine** (already exists!): ```rust // From ruvector-postgres/src/graph/sparql/ pub use crate::graph::sparql::{ parse_sparql, execute_sparql, TripleStore, }; // Example: // SELECT ?subject ?label WHERE { // ?subject rdfs:label ?label . // FILTER vector:similar(?subject, ?query_vector, 0.8) // } ``` **Cypher Engine** (already exists!): ```rust // From ruvector-postgres/src/graph/cypher/ pub use crate::graph::cypher::{ parse_cypher, execute_cypher, }; // Example: // MATCH (a:Person)-[:KNOWS]->(b:Person) // WHERE vector.cosine(a.embedding, $query) > 0.8 // RETURN a, b ``` #### 3. WASM Bindings (`ruvector-wasm/src/lib.rs`) ```rust use wasm_bindgen::prelude::*; #[wasm_bindgen] pub struct RuVector { db: Arc, } #[wasm_bindgen] impl RuVector { /// Create a new in-memory database #[wasm_bindgen(constructor)] pub fn new() -> Result { Ok(RuVector { db: Arc::new(Database::new()), }) } /// Execute SQL query #[wasm_bindgen(js_name = executeSql)] pub async fn execute_sql(&self, query: &str) -> Result { let results = self.db.execute_sql(query).await?; Ok(serde_wasm_bindgen::to_value(&results)?) } /// Execute SPARQL query #[wasm_bindgen(js_name = executeSparql)] pub async fn execute_sparql(&self, query: &str) -> Result { let results = self.db.execute_sparql(query).await?; Ok(serde_wasm_bindgen::to_value(&results)?) } /// Execute Cypher query #[wasm_bindgen(js_name = executeCypher)] pub async fn execute_cypher(&self, query: &str) -> Result { let results = self.db.execute_cypher(query).await?; Ok(serde_wasm_bindgen::to_value(&results)?) } /// Insert vectors #[wasm_bindgen(js_name = insertVectors)] pub async fn insert_vectors( &self, table: &str, vectors: Vec, metadata: JsValue, ) -> Result<(), JsValue> { // Implementation Ok(()) } /// Vector similarity search #[wasm_bindgen(js_name = searchSimilar)] pub async fn search_similar( &self, table: &str, query_vector: Vec, limit: usize, ) -> Result { // Implementation Ok(serde_wasm_bindgen::to_value(&results)?) } /// Save database to storage #[wasm_bindgen(js_name = save)] pub async fn save(&self) -> Result<(), JsValue> { self.db.persist().await?; Ok(()) } /// Load database from storage #[wasm_bindgen(js_name = load)] pub async fn load() -> Result { let db = Database::load().await?; Ok(RuVector { db: Arc::new(db) }) } } ``` #### 4. TypeScript API (`npm/packages/wasm/src/index.ts`) ```typescript export class RuVector { private db: WasmRuVector; static async create(options?: DatabaseOptions): Promise { await init(); // Load WASM const db = new WasmRuVector(); return new RuVector(db); } // SQL interface async sql(query: string, params?: any[]): Promise { return await this.db.executeSql(query); } // SPARQL interface async sparql(query: string): Promise { return await this.db.executeSparql(query); } // Cypher interface async cypher(query: string): Promise { return await this.db.executeCypher(query); } // Convenience methods async insertVectors(table: string, data: VectorData[]): Promise { // Batch insert } async searchSimilar( table: string, queryVector: Float32Array, options?: SearchOptions ): Promise { return await this.db.searchSimilar(table, queryVector, options.limit); } // Persistence async save(): Promise { await this.db.save(); } static async load(): Promise { await init(); const db = await WasmRuVector.load(); return new RuVector(db); } } // Export types export type { VectorData, SearchResult, SearchOptions, SparqlResults, CypherResults }; ``` --- ## πŸ“¦ Project Structure ``` ruvector/ β”œβ”€β”€ crates/ β”‚ β”œβ”€β”€ ruvector-core/ # Shared core (NO PostgreSQL deps) β”‚ β”‚ β”œβ”€β”€ types/ # Vector types β”‚ β”‚ β”œβ”€β”€ distance/ # Distance metrics β”‚ β”‚ β”œβ”€β”€ index/ # HNSW, IVF β”‚ β”‚ β”œβ”€β”€ quantization/ # Binary, scalar, product β”‚ β”‚ └── simd/ # WASM SIMD β”‚ β”‚ β”‚ β”œβ”€β”€ ruvector-wasm/ # NEW: Standalone WASM database β”‚ β”‚ β”œβ”€β”€ Cargo.toml # wasm-bindgen, wasm-pack β”‚ β”‚ β”œβ”€β”€ src/ β”‚ β”‚ β”‚ β”œβ”€β”€ lib.rs # WASM bindings β”‚ β”‚ β”‚ β”œβ”€β”€ storage/ # In-memory + persistence β”‚ β”‚ β”‚ β”œβ”€β”€ query/ # SQL/SPARQL/Cypher engines β”‚ β”‚ β”‚ β”œβ”€β”€ graph/ # Graph operations (from postgres) β”‚ β”‚ β”‚ β”œβ”€β”€ learning/ # ReasoningBank (from postgres) β”‚ β”‚ β”‚ β”œβ”€β”€ gnn/ # GNN layers (from postgres) β”‚ β”‚ β”‚ └── hyperbolic/ # Hyperbolic spaces (from postgres) β”‚ β”‚ └── tests/ β”‚ β”‚ β”‚ └── ruvector-postgres/ # Existing PostgreSQL extension β”‚ └── ... (unchanged) β”‚ β”œβ”€β”€ npm/ β”‚ └── packages/ β”‚ β”œβ”€β”€ wasm/ # NEW: @ruvector/wasm β”‚ β”‚ β”œβ”€β”€ package.json β”‚ β”‚ β”œβ”€β”€ src/ β”‚ β”‚ β”‚ β”œβ”€β”€ index.ts # TypeScript API β”‚ β”‚ β”‚ β”œβ”€β”€ types.ts # Type definitions β”‚ β”‚ β”‚ └── workers/ # Web Worker support β”‚ β”‚ β”œβ”€β”€ dist/ β”‚ β”‚ β”‚ β”œβ”€β”€ ruvector_bg.wasm β”‚ β”‚ β”‚ β”œβ”€β”€ index.js β”‚ β”‚ β”‚ └── index.d.ts β”‚ β”‚ └── examples/ β”‚ β”‚ β”œβ”€β”€ browser.html β”‚ β”‚ β”œβ”€β”€ node.js β”‚ β”‚ β”œβ”€β”€ deno.ts β”‚ β”‚ └── cloudflare-worker.js β”‚ β”‚ β”‚ └── ... (existing packages) β”‚ └── docs/ β”œβ”€β”€ RUVECTOR_WASM_QUICKSTART.md β”œβ”€β”€ SQL_API.md β”œβ”€β”€ SPARQL_API.md β”œβ”€β”€ CYPHER_API.md └── DEPLOYMENT_GUIDE.md ``` --- ## πŸš€ Implementation Plan ### Phase 1: Core Extraction (Week 1-2) **Extract from `ruvector-postgres`** to create standalone `ruvector-core`: ```toml # crates/ruvector-core/Cargo.toml [package] name = "ruvector-core" version = "0.1.0" [lib] crate-type = ["lib"] [features] default = ["std"] std = [] # Standard library wasm = ["wasm-bindgen"] # WASM support [dependencies] # NO PostgreSQL dependencies! half = { version = "2.4", default-features = false } simsimd = { version = "5.9", default-features = false } serde = { version = "1.0", default-features = false, features = ["alloc"] } dashmap = "6.0" [target.'cfg(target_arch = "wasm32")'.dependencies] wasm-bindgen = { version = "0.2", optional = true } ``` **Move these modules** (already written!): - `types/` β†’ Vector types (no changes needed) - `distance/` β†’ Distance metrics (remove pgrx deps) - `index/hnsw.rs` β†’ HNSW index (remove pgrx deps) - `quantization/` β†’ Quantization (no changes) - `graph/` β†’ SPARQL, Cypher (remove pgrx, add standalone storage) - `learning/` β†’ ReasoningBank (remove pgrx deps) - `gnn/` β†’ GNN layers (remove pgrx deps) - `hyperbolic/` β†’ Hyperbolic spaces (no changes) ### Phase 2: Storage Engine (Week 3) **Create in-memory database**: ```rust // ruvector-wasm/src/storage/database.rs use dashmap::DashMap; use parking_lot::RwLock; pub struct Database { tables: DashMap, triple_store: Arc, graph: Arc, } pub struct Table { schema: Schema, rows: RwLock>, vector_index: Option, } impl Database { pub fn create_table(&self, name: &str, schema: Schema) { self.tables.insert(name.to_string(), Table::new(schema)); } pub fn insert(&self, table: &str, row: Row) -> Result<()> { let table = self.tables.get(table)?; table.rows.write().push(row); // Update vector index if present if let Some(idx) = &table.vector_index { idx.insert(row.vector)?; } Ok(()) } pub fn search_similar( &self, table: &str, query: &[f32], k: usize, ) -> Result> { let table = self.tables.get(table)?; let idx = table.vector_index.as_ref()?; let ids = idx.search(query, k)?; let rows = table.rows.read(); Ok(ids.iter().map(|&id| rows[id].clone()).collect()) } } ``` **Add persistence backends**: ```rust // ruvector-wasm/src/storage/persist.rs #[cfg(target_arch = "wasm32")] mod browser { use wasm_bindgen::prelude::*; use web_sys::{IdbDatabase, IdbObjectStore}; pub async fn save_to_indexeddb(db: &Database) -> Result<()> { let idb = open_indexeddb("ruvector").await?; // Serialize database to IndexedDB Ok(()) } } #[cfg(not(target_arch = "wasm32"))] mod node { use std::fs; use bincode; pub async fn save_to_file(db: &Database, path: &str) -> Result<()> { let bytes = bincode::serialize(db)?; fs::write(path, bytes)?; Ok(()) } } ``` ### Phase 3: Query Engines (Week 4-5) **SQL Executor**: ```rust // ruvector-wasm/src/query/sql.rs pub struct SqlExecutor { db: Arc, } impl SqlExecutor { pub async fn execute(&self, query: &str) -> Result { let ast = parse_sql(query)?; match ast { Statement::Select(select) => self.execute_select(select).await, Statement::Insert(insert) => self.execute_insert(insert).await, Statement::CreateTable(create) => self.execute_create(create).await, _ => todo!(), } } async fn execute_select(&self, select: Select) -> Result { // Vector similarity: ORDER BY embedding <=> $1 if let Some(order) = &select.order_by { if order.op == VectorDistance { return self.vector_search(select).await; } } // Standard SELECT self.scan_table(select).await } } ``` **SPARQL Executor** (already exists, just adapt!): ```rust // Already in ruvector-postgres/src/graph/sparql/executor.rs // Just remove pgrx dependencies and use our Database instead pub async fn execute_sparql( db: &Database, query: &str, ) -> Result { let ast = parse_sparql(query)?; match ast.query_form { QueryForm::Select => execute_select(db, ast).await, QueryForm::Construct => execute_construct(db, ast).await, // ... already implemented! } } ``` **Cypher Executor** (already exists!): ```rust // Already in ruvector-postgres/src/graph/cypher/executor.rs pub async fn execute_cypher( db: &Database, query: &str, ) -> Result { // Already implemented, just adapt to our Database } ``` ### Phase 4: WASM Compilation (Week 6) **Configure for WASM**: ```toml # ruvector-wasm/Cargo.toml [package] name = "ruvector-wasm" version = "0.1.0" [lib] crate-type = ["cdylib"] # For WASM [dependencies] ruvector-core = { path = "../ruvector-core", features = ["wasm"] } wasm-bindgen = "0.2" wasm-bindgen-futures = "0.4" serde-wasm-bindgen = "0.6" js-sys = "0.3" web-sys = { version = "0.3", features = ["Window", "IdbDatabase", "IdbObjectStore"] } [profile.release] opt-level = "z" # Optimize for size lto = true # Link-time optimization codegen-units = 1 # Single codegen unit ``` **Build script**: ```bash #!/bin/bash # scripts/build-wasm.sh echo "Building ruvector-wasm..." # Install wasm-pack cargo install wasm-pack # Build for web wasm-pack build crates/ruvector-wasm \ --target web \ --out-dir ../../npm/packages/wasm/dist \ --release # Build for Node.js wasm-pack build crates/ruvector-wasm \ --target nodejs \ --out-dir ../../npm/packages/wasm/dist-node \ --release # Size report echo "WASM size:" du -h npm/packages/wasm/dist/ruvector_bg.wasm ``` ### Phase 5: NPM Package (Week 7) **TypeScript wrapper**: ```typescript // npm/packages/wasm/src/index.ts import init, { RuVector as WasmRuVector, InitOutput } from '../dist/ruvector_wasm'; let wasmInit: Promise | null = null; async function ensureInit(): Promise { if (!wasmInit) { wasmInit = init(); } await wasmInit; } export class RuVector { private db: WasmRuVector; private constructor(db: WasmRuVector) { this.db = db; } static async create(options?: DatabaseOptions): Promise { await ensureInit(); const db = new WasmRuVector(); return new RuVector(db); } async sql(query: string): Promise { const result = await this.db.executeSql(query); return JSON.parse(result); } async sparql(query: string): Promise { const result = await this.db.executeSparql(query); return JSON.parse(result); } async cypher(query: string): Promise { const result = await this.db.executeCypher(query); return JSON.parse(result); } async close(): Promise { // Cleanup } } export * from './types'; ``` **Package configuration**: ```json { "name": "@ruvector/wasm", "version": "0.1.0", "description": "Standalone vector database with SQL/SPARQL/Cypher - runs anywhere", "type": "module", "main": "./dist/index.js", "types": "./dist/index.d.ts", "exports": { ".": { "types": "./dist/index.d.ts", "import": "./dist/index.js", "require": "./dist/index.cjs" }, "./node": { "types": "./dist-node/index.d.ts", "import": "./dist-node/index.js" } }, "files": ["dist", "dist-node"], "keywords": [ "vector-database", "wasm", "graph-database", "sparql", "cypher", "sql", "semantic-search", "embeddings" ], "engines": { "node": ">=18.0.0" } } ``` ### Phase 6: Examples & Documentation (Week 8) **Browser example**: ```html RuVector WASM Demo

Standalone Vector Database in Your Browser!

``` --- ## πŸ“Š Size Budget | Component | Size | Cumulative | |-----------|------|------------| | Core WASM runtime | ~500KB | 500KB | | Vector operations + SIMD | ~300KB | 800KB | | HNSW index | ~400KB | 1.2MB | | SQL parser & executor | ~600KB | 1.8MB | | SPARQL engine | ~800KB | 2.6MB | | Cypher engine | ~600KB | 3.2MB | | Graph operations | ~400KB | 3.6MB | | GNN layers | ~800KB | 4.4MB | | ReasoningBank learning | ~600KB | 5.0MB | | Hyperbolic spaces | ~300KB | 5.3MB | | **Total (gzipped)** | | **~5-6MB** | **Comparison**: - DuckDB-WASM: ~6-8MB - SQLite-WASM: ~1MB (no vector/graph features) - PGlite: ~3MB (minimal Postgres, no vector by default) - **RuVector-WASM: ~5-6MB** (FULL features!) --- ## 🎯 Success Metrics | Metric | Target | |--------|--------| | Bundle size (gzipped) | < 6MB | | Load time (browser) | < 1s | | Query latency (1k vectors) | < 20ms | | Memory usage (100k vectors) | < 200MB | | Browser support | Chrome 91+, Firefox 89+, Safari 16.4+ | | Node.js support | 18+ | --- ## πŸš€ Usage Examples ### Browser - Semantic Search ```typescript import { RuVector } from '@ruvector/wasm'; // Create database const db = await RuVector.create(); // Setup schema await db.sql(` CREATE TABLE articles ( id SERIAL PRIMARY KEY, title TEXT, content TEXT, embedding VECTOR(768) ) `); // Insert with embeddings await db.insertVectors('articles', [ { title: 'AI in 2025', content: '...', embedding: await getEmbedding('AI in 2025') }, // ... more articles ]); // Semantic search const results = await db.searchSimilar( 'articles', queryEmbedding, { limit: 10, threshold: 0.7 } ); ``` ### Node.js - Knowledge Graph ```typescript import { RuVector } from '@ruvector/wasm/node'; const db = await RuVector.create(); // Cypher: Create knowledge graph await db.cypher(` CREATE (a:Person {name: 'Alice', embedding: $a_emb}) CREATE (b:Person {name: 'Bob', embedding: $b_emb}) CREATE (a)-[:KNOWS]->(b) `, { a_emb: aliceEmbedding, b_emb: bobEmbedding }); // Cypher: Find similar people await db.cypher(` MATCH (p:Person) WHERE vector.cosine(p.embedding, $query) > 0.8 RETURN p.name `); ``` ### Cloudflare Workers - Edge Search ```typescript import { RuVector } from '@ruvector/wasm'; export default { async fetch(request: Request, env: Env) { const db = await RuVector.create(); // Load from Durable Object or KV // await db.load(); const { query } = await request.json(); const embedding = await generateEmbedding(query); const results = await db.sql(` SELECT * FROM products ORDER BY embedding <=> $1 LIMIT 10 `, [embedding]); return Response.json(results); } }; ``` ### Deno - SPARQL RDF Store ```typescript import { RuVector } from "https://esm.sh/@ruvector/wasm"; const db = await RuVector.create(); // SPARQL: Query RDF data const results = await db.sparql(` PREFIX foaf: PREFIX vec: SELECT ?person ?name ?similarity WHERE { ?person foaf:name ?name . BIND(vec:cosine(?person, ?query) AS ?similarity) FILTER(?similarity > 0.8) } ORDER BY DESC(?similarity) LIMIT 10 `); ``` --- ## πŸ“… 8-Week Timeline | Week | Milestone | |------|-----------| | 1-2 | Extract `ruvector-core`, remove PostgreSQL deps | | 3 | Build storage engine (in-memory + persistence) | | 4-5 | Adapt query engines (SQL, SPARQL, Cypher) | | 6 | WASM compilation, optimization, testing | | 7 | NPM package, TypeScript API, CI/CD | | 8 | Documentation, examples, beta release | --- ## βœ… Advantages Over PGlite Extension | Feature | PGlite Extension | RuVector-WASM | |---------|------------------|---------------| | PostgreSQL dependency | βœ… Included (3MB) | ❌ None | | Full ruvector features | ❌ Limited (size) | βœ… All features | | SPARQL/Cypher | ❌ Hard to add | βœ… Built-in | | GNN/Learning | ❌ Too large | βœ… Included | | Build complexity | ❌ Emscripten + PGlite fork | βœ… wasm-pack only | | Maintenance | ❌ Track PGlite updates | βœ… Independent | | Size | ~3MB + extension | ~5-6MB total | --- **Ready to build the future of vector databases?** πŸš€ This is the RIGHT architecture for your vision!