vector datauases

Part of BlackRoad OS — Sovereign Computing for Everyone

vector datauases is part of the BlackRoad OS ecosystem — a sovereign, distributed operating system built on edge computing, local AI, and mesh networking by BlackRoad OS, Inc.

About BlackRoad OS

BlackRoad OS is a sovereign computing platform that runs AI locally on your own hardware. No cloud dependencies. No API keys. No surveillance. Built by BlackRoad OS, Inc., a Delaware C-Corp founded in 2025.

Key Features

• Local AI — Run LLMs on Raspberry Pi, Hailo-8, and commodity hardware
• Mesh Networking — WireGuard VPN, NATS pub/sub, peer-to-peer communication
• Edge Computing — 52 TOPS of AI acceleration across a Pi fleet
• Self-Hosted Everything — Git, DNS, storage, CI/CD, chat — all sovereign
• Zero Cloud Dependencies — Your data stays on your hardware

The BlackRoad Ecosystem

Organization	Focus
BlackRoad OS	Core platform and applications
BlackRoad OS, Inc.	Corporate and enterprise
BlackRoad AI	Artificial intelligence and ML
BlackRoad Hardware	Edge hardware and IoT
BlackRoad Security	Cybersecurity and auditing
BlackRoad Quantum	Quantum computing research
BlackRoad Agents	Autonomous AI agents
BlackRoad Network	Mesh and distributed networking
BlackRoad Education	Learning and tutoring platforms
BlackRoad Labs	Research and experiments
BlackRoad Cloud	Self-hosted cloud infrastructure
BlackRoad Forge	Developer tools and utilities

Links

• Website: blackroad.io
• Documentation: docs.blackroad.io
• Chat: chat.blackroad.io
• Search: search.blackroad.io

---

Embedding storage and similarity search for AI workloads

Supported Databases

Database	Use Case	Scale	Performance
Milvus	Production clusters	Billions	High
pgvector	PostgreSQL native	Millions	Good
LanceDB	Serverless/Edge	Millions	Fast
Faiss	In-memory	Billions	Fastest

Quick Start

Milvus (Distributed)

docker compose -f milvus/docker-compose.yml up -d

pgvector (PostgreSQL)

CREATE EXTENSION vector;
CREATE TABLE embeddings (id serial, embedding vector(1536));

LanceDB (Serverless)

import lancedb
db = lancedb.connect("./blackroad-vectors")

Faiss (In-Memory)

import faiss
index = faiss.IndexFlatL2(1536)

Architecture

┌─────────────────────────────────────────────────────────┐
│                   BlackRoad AI Layer                     │
├─────────────┬─────────────┬─────────────┬──────────────┤
│   Milvus    │  pgvector   │  LanceDB    │    Faiss     │
│  (Cluster)  │ (Postgres)  │ (Serverless)│  (In-Memory) │
└─────────────┴─────────────┴─────────────┴──────────────┘

Embedding Models

Model	Dimensions	Use Case
text-embedding-3-large	3072	High accuracy
text-embedding-3-small	1536	Balanced
BGE-M3	1024	Multilingual
all-MiniLM-L6-v2	384	Fast/lightweight

---

BlackRoad OS - Vector Intelligence at Scale