skills.rest
ricable
ricableCOMMUNITY
Explore all skills by this author →
GitHub

@ruvector/rvlite

Run embedded vector searches with SQL, SPARQL, and Cypher via WASM.

1|Updated Feb 8, 2026
Search Tags:#search#vector database#sql#embedded#wasm#cypher#sparql
One-click install
npx skills add https://github.com/ricable/cli-skills-builder --skill ruvector-rvlite
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: @ruvector/rvlite
Source: https://github.com/ricable/cli-skills-builder/tree/main/.claude/skills/ruvector-rvlite
Command: npx skills add https://github.com/ricable/cli-skills-builder --skill ruvector-rvlite

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a lightweight, embedded vector database that allows for powerful vector search and data querying directly within applications without external dependencies.

Core Features & Use Cases

  • Standalone Vector Search: Perform vector similarity searches in any JavaScript runtime.
  • Multi-Language Querying: Supports SQL, SPARQL, and Cypher for flexible data interaction.
  • Zero Dependencies: Runs via WebAssembly (WASM) for portability.
  • Use Case: Integrate a fast, embedded search engine into your web application or Node.js script to find similar items based on vector embeddings, while also allowing structured queries on the associated metadata.

Quick Start

Initialize a new RVLite database instance with default settings.

Frequently Asked Questions about @ruvector/rvlite

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run an embedded vector database in a JavaScript application without external dependencies?▼

You can use an embedded vector database powered by WebAssembly to run vector search directly in JavaScript environments with zero external dependencies. This approach provides standalone vector similarity search and data querying across any JS runtime.

Can I query vector search results using SQL, Cypher, and SPARQL simultaneously?▼

Yes, multi-language querying supports SQL, Cypher, and SPARQL for flexible data interaction. This allows you to perform vector similarity searches while executing structured queries on the associated metadata within the same embedded database.

What is the best way to add zero-dependency vector search to a Node.js script?▼

The best way to add zero-dependency vector search is using a WebAssembly-based embedded vector database. It enables fast, portable vector stores and similarity searches in Node.js without requiring external database servers or heavy installations.

Does WebAssembly vector database support cross-runtime compatibility in JavaScript environments?▼

WebAssembly vector database support ensures cross-runtime compatibility in JavaScript environments. By utilizing WASM, the embedded vector store operates portably across different JavaScript runtimes without needing environment-specific dependencies.

How do I initialize a standalone vector database instance for web applications?▼

To initialize a standalone vector database instance, configure the embedded WASM-powered database with default settings. This quick start approach allows immediate integration of vector search and structured querying into your web application.

When should I not use an embedded WASM vector database for my application?▼

You should not use an embedded WASM vector database if your application requires distributed data storage or massive concurrent write scaling beyond a single runtime. It is designed for lightweight, standalone vector search rather than enterprise-level distributed database workloads.

Related Skills

Explore More Software Engineering Skills→
lewisperez999lewisperez999

vector-embeddings

Generate text embeddings with OpenAI and search by cosine similarity in Upstash Vector or pg-vector.

Community
Intermediate
just-cameronjust-cameron
23

using-xrpc-indexer

Queries cognition records via comind's network.search API with vector similarity across concepts, thoughts, memories, hypotheses.

Community
Intermediate
Clay-HHKClay-HHK
2

chroma

Store embeddings and metadata for semantic and full-text retrieval.

Community
Intermediate
ChimeraFoundationaChimeraFoundationa

qdrant-vector-search

Index and search vector data with HNSW and payload filtering via REST and gRPC.

Community
Advanced