Skardi

SQL across anything — query, join, and aggregate over local files, databases, S3, and vector stores, or turn any SQL into a parameterized HTTP API with zero application code. Written in Rust, powered by Apache DataFusion.

Quick Start

A product-search-demo pipeline is pre-loaded when you first launch the instance. Use it to verify everything is working:

# List all registered pipelines
curl https://<your-app-host>/pipelines

# Run the demo pipeline — returns products filtered by price, brand, category, etc.
curl -X POST https://<your-app-host>/product-search-demo/execute \
  -H "Content-Type: application/json" \
  -d '{
    "brand": null,
    "max_price": 50.0,
    "min_price": null,
    "color": null,
    "category": null,
    "availability": null,
    "limit": 10
  }'

All parameters are optional — pass null to skip a filter.

Customizing Your Deployment

Skardi is configured via two YAML files mounted from ConfigMaps:

Edit the ConfigMaps through the Sealos dashboard or with kubectl, then restart the pod to apply changes.

Example: Adding a PostgreSQL Data Source

# ctx.yaml
data_sources:
  - name: "users"
    type: "postgres"
    connection_string: "postgresql://localhost:5432/mydb?sslmode=disable"
    options:
      table: "users"
      user_env: "PG_USER"
      pass_env: "PG_PASSWORD"

Example: Defining a Pipeline

# pipeline.yaml
metadata:
  name: user-lookup
  version: 1.0.0

query: |
  SELECT id, name, email
  FROM users
  WHERE id = {user_id}

Execute it:

curl -X POST https://<your-app-host>/user-lookup/execute \
  -H "Content-Type: application/json" \
  -d '{"user_id": 42}'

API Endpoints

Supported Data Sources

CSV · Parquet · JSON · PostgreSQL · MySQL · SQLite · MongoDB · Redis · Apache Iceberg · Lance (vector + full-text search) · S3 / GCS / Azure Blob

Links

• GitHub
• Documentation