HeliosDB Quick Start Guide

HeliosDB Quick Start Guide

Get started with HeliosDB in 5 minutes!

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What is HeliosDB?

HeliosDB is a next-generation distributed database combining:

• Postgres-compatible SQL with advanced extensions
• 🧠 AI-powered optimization (NL2SQL, autonomous indexing, ML compression)
• Post-quantum cryptography for future-proof security
• Hybrid vector search (dense + sparse + learned fusion)
• Real-time streaming with Flink integration
• Edge computing with WASM procedures

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Installation

Option 1: Quick Install (Recommended)

# Clone the repository
git clone https://github.com/your-org/HeliosDB.git
cd HeliosDB

# Build the database
cargo build --release

# Run HeliosDB server
./target/release/heliosdb-server

Option 2: Docker

# Pull the latest image
docker pull heliosdb/heliosdb:latest

# Run the container
docker run -p 5432:5432 heliosdb/heliosdb:latest

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Your First Database

1. Connect to HeliosDB

# Using psql (Postgres-compatible)
psql -h localhost -p 5432 -U heliosdb

2. Create a Table

CREATE TABLE users (
    id SERIAL PRIMARY KEY,
    name TEXT NOT NULL,
    email TEXT UNIQUE,
    created_at TIMESTAMP DEFAULT NOW()
);

3. Insert Data

INSERT INTO users (name, email) VALUES
    ('Alice', 'alice@example.com'),
    ('Bob', 'bob@example.com'),
    ('Charlie', 'charlie@example.com');

4. Query Data

SELECT * FROM users WHERE name LIKE 'A%';

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Advanced Features (5-Minute Intro)

Natural Language Queries (NL2SQL)

-- Use natural language!
SELECT nl2sql('Show me all users created in the last 7 days');

Vector Search

-- Enable hybrid search
CREATE TABLE documents (
    id SERIAL PRIMARY KEY,
    content TEXT,
    embedding VECTOR(768)
);

-- Hybrid search (dense + sparse + learned fusion)
SELECT * FROM documents
WHERE content @@@ 'machine learning'
ORDER BY embedding <=> vector('[0.1, 0.2, ...]')
LIMIT 10;

Real-Time Streaming

-- Create a streaming table
CREATE STREAM clickstream (
    user_id INT,
    event TEXT,
    timestamp TIMESTAMP
);

-- Real-time aggregation
SELECT
    window_start,
    COUNT(*) as events_per_minute
FROM clickstream
GROUP BY TUMBLE(timestamp, INTERVAL '1 minute');

AI Compression

-- Enable ML-driven compression
ALTER TABLE large_table
SET COMPRESSION = 'ai_adaptive';

-- HeliosDB learns optimal codec per column!

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Next Steps

Choose your learning path:

📚 Comprehensive Guides

• Getting Started: docs/quick-starts/01-quickstart.md
• Detailed Tutorial: docs/quick-starts/05-getting-started-detailed.md
• User Guide Index: docs/USER_GUIDE_INDEX.md

Feature-Specific Quick Starts

• Vector Search: docs/quick-starts/09-vector-quickstart.md
• Geospatial: docs/quick-starts/10-geospatial-quickstart.md
• Arrow Flight: docs/quick-starts/15-arrow-flight-quickstart.md
• Java Client: docs/quick-starts/11-java-quickstart.md
• CLI Tools: docs/quick-starts/07-cli-quick-start.md

Advanced Features

• Streaming & Real-Time: docs/guides/user-guide/F1.3_STREAMING_GUIDE.md
• AI Compression: docs/guides/features/AI_COMPRESSION_GUIDE.md
• Post-Quantum Crypto: docs/guides/user-guide/F6.11_PQC_GUIDE.md
• WASM Edge Functions: docs/implementation/v6.0/F6.12_F6.13_WASM_IMPLEMENTATION_REPORT.md

🎓 In-Depth Documentation

• Architecture: docs/architecture/
• API Reference: docs/api/
• User Guides: docs/user-guides/
• Roadmap: docs/ROADMAP.md

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Example: Build a Simple App

Python Example

import psycopg2

# Connect to HeliosDB
conn = psycopg2.connect(
    host="localhost",
    port=5432,
    user="heliosdb",
    database="myapp"
)

# Create cursor
cur = conn.cursor()

# Natural language query
cur.execute("SELECT nl2sql('Find all orders over $100 from last month')")
results = cur.fetchall()

print(results)

# Close connection
cur.close()
conn.close()

Node.js Example

const { Client } = require('pg');

const client = new Client({
  host: 'localhost',
  port: 5432,
  user: 'heliosdb',
  database: 'myapp'
});

await client.connect();

// Hybrid vector search
const query = `
  SELECT * FROM products
  WHERE description @@@ $1
  ORDER BY embedding <=> $2
  LIMIT 10
`;

const result = await client.query(query, [
  'wireless headphones',
  '[0.1, 0.2, ...]'
]);

console.log(result.rows);

await client.end();

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Common Commands

# Start HeliosDB server
heliosdb-server --config config.toml

# Run tests
cargo test

# Check status
heliosdb-cli status

# View logs
tail -f logs/heliosdb.log

# Backup database
heliosdb-cli backup --output backup.tar.gz

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Getting Help

• 📖 Documentation: docs/
• 💬 Community: Discord | GitHub Discussions
• 🐛 Issues: GitHub Issues
• 📧 Email: support@heliosdb.com

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What Makes HeliosDB Special?

Feature	Traditional DBs	HeliosDB
Natural Language Queries	❌	World’s first Agentic NL2SQL
Post-Quantum Security	❌	NIST Kyber-768 ready
Hybrid Vector Search	Partial	Dense + Sparse + Learned Fusion
AI Compression	Static	ML-driven adaptive codecs
Edge Computing	❌	WASM procedures & functions
Real-Time Streaming	Separate tools	Native Flink integration
Autonomous Optimization	Manual	Self-tuning indexes & queries

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Performance Highlights

• Sub-10ms TLS handshake (post-quantum)
• +40% relevance improvement (hybrid search)
• 4.5x compression ratio (AI-driven)
• 90% DBA time reduction (autonomous indexing)
• 💰 30% cost reduction (workload optimizer)

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Ready to Dive Deeper?

Start with the comprehensive getting started guide:

👉 docs/quick-starts/01-quickstart.md

Or explore the full feature index:

👉 docs/USER_GUIDE_INDEX.md

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Welcome to HeliosDB - The Future of Databases!