lance Docker & Self-Hosted Deployment

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Open Lakehouse Format for Multimodal AI. Convert from Parquet in 2 lines of code for 100x faster random access, vector index, and data versioning.

6,904 stars Rust Rust 1 file · ~3,502 tokens #apache-arrow#computer-vision#data-analysis#data-analytics#data-centric#data-format#data-science#dataops
RAW Compose
1. Pull Image (DOCKERHUB) docker pull localstack/localstack
2. Docker Run (1-Click Launch) docker run -d --name lance -p 4566:4566 --restart always localstack/localstack:4.0
3. Podman Run podman run -d --name lance -p 4566:4566 --restart always localstack/localstack:4.0
4. Skopeo Inspect (Zero-Pull Manifest) skopeo inspect docker://docker.io/localstack/localstack:4.0
5. ORAS Pull (OCI Artifact) oras pull localstack/localstack:4.0
6. Compose Deployment docker compose up -d
docker-compose.yml
Download .yml 
version: "3.9"
services:
  localstack:
    image: localstack/localstack:4.0
    ports:
      - 4566:4566
    environment:
      - SERVICES=s3,dynamodb,kms
      - DOCKER_HOST=unix:///var/run/docker.sock
      # Note: localstack doesn't actually validate these.
      - AWS_ACCESS_KEY_ID=ACCESS_KEY
      - AWS_SECRET_ACCESS_KEY=SECRET_KEY
    healthcheck:
      test: [ "CMD", "curl", "-s", "http://localhost:4566/_localstack/health" ]
      interval: 5s
      retries: 3
      start_period: 10s