🚀 LeverSQL - Coming Soon - Developer-First Database

The Future of Databases is LeverSQL

Lightweight yet infinitely scalable. Experience the next generation database built for modern applications with built-in sharding, replication, and vector support.

Powerful Features, Simplified Experience

LeverSQL combines enterprise-grade capabilities with developer-friendly interfaces

Lightweight & Scalable

Start small and scale infinitely. LeverSQL adapts to your needs without compromising on performance.

🔄

Automatic Sharding

Distribute your data across multiple files automatically for optimal performance and reliability.

📊

Async Replication

Create asynchronous copies of your data with S3-compatible storage for enhanced reliability.

🔄

Non-blocking Operations

Read the most recent data while batching writes for optimal throughput and responsiveness.

Reversibility

Unique "undo" query capability lets you revert changes safely and confidently.

📱

Intelligent Dashboard

Powerful management interface with built-in AI capabilities for local querying.

🛡️

DDOS Protection

Advanced safeguards with IP filtering and token-based security to keep your data safe.

🔌

Built-in ORM

Seamlessly interact with your data using our intuitive object-relational mapping.

🔑

Auth Middleware

Integrated authentication system that works right out of the box.

🧠

Vector Embeddings

Native support for AI vector operations and similarity searches.

Built-in Cache

Optimize performance with intelligent caching strategies baked right in.

📋

Built-in Queue

Handle background tasks and job processing without additional infrastructure.

Built for Modern Development

LeverSQL brings enterprise capabilities to teams of all sizes. Our database combines the simplicity developers love with the power that modern applications demand.

10x
Faster Queries
50%
Less Code
Scalability
// Import and configure LeverSQL
import { LeverSQL } from '@leverscale/leversql';

// Initialize with smart defaults
const db = new LeverSQL({
  sharding: {
    enabled: true,
    strategy: 'auto'
  },
  replication: {
    enabled: true,
    storage: 's3',
    async: true
  },
  cache: { ttl: '5m' },
  queue: { workers: 4 }
});

// Define a model with vectors
const Product = db.model('Product', {
  name: String,
  description: String,
  price: Number,
  embedding: LeverSQL.Vector(1536)
});

// Vector similarity search
const results = await Product.findSimilar({
  vector: embeddings,
  minSimilarity: 0.75
}).limit(10);