GeoLens

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Your team's spatial data: searchable, mappable, and shareable in one place.

GeoLens is an open-source, self-hosted catalog and map builder for GIS and data teams: a single home for spatial data that you run on infrastructure you control, with no telemetry. GeoLens itself phones home to nothing. (Features you opt into can make outbound calls: AI assist to your chosen OpenAI-compatible endpoint or Anthropic key, OAuth/OIDC sign-in, SMTP, basemap tiles, remote/S3 data sources, and off-site backups.) Upload Shapefiles, GeoTIFFs, GeoPackages, or CSVs (or register data you already have); GeoLens stores everything in PostGIS, indexes it with pg_trgm for fuzzy search out of the box (pgvector adds semantic ranking once you configure an embedding provider and enable semantic search), and serves OGC/STAC APIs that QGIS, ArcGIS, and MapLibre clients connect to natively. Compose, style, and share multi-layer maps right in the browser. Built on FastAPI and React. Deployed with one command.

_{No install required. Browse the sample catalog and maps without an account, or sign in with Google, GitHub, or Microsoft to try the map builder. Demo data may be wiped at any time.}

curl -fsSL https://getgeolens.com/install.sh | sh
# Open http://localhost:8080, then log in with the credentials you chose

The map builder: every Manhattan building extruded to its true roof height and colored by the era it was built, the subway threading beneath, built from open data with scripts/seed-showcase.py

Note

Early release. GeoLens is actively developed and maintained, and newly open-sourced. The core has run in production, but the self-hosted distribution is young and some features and APIs may still change. Please open an issue if you hit a rough edge.

Documentation

Full user, admin, and API documentation lives at docs.getgeolens.com. The Reference table below links each guide.

Published artifacts

GeoLens is published through the standard package registries:

pip install geolens          # Python SDK
pip install geolens-cli      # CLI; installs the `geolens` command
npm install @geolens/sdk     # TypeScript/JavaScript SDK

Prebuilt public API and frontend images are published to GitHub Container Registry:

docker pull ghcr.io/geolens-io/geolens-api:latest
docker pull ghcr.io/geolens-io/geolens-frontend:latest

The latest tag tracks the newest published stable release.

Why GeoLens?

Spatial data ends up scattered: shapefiles on shared drives, tables in database schemas, rasters in cloud buckets, metadata in spreadsheets. Finding the right dataset means asking Slack or grepping file servers. Sharing it means exporting, emailing, and hoping the CRS matches.

GeoLens replaces that workflow:

• One catalog: upload Shapefiles, GeoPackages, GeoTIFFs, or CSVs and they become searchable, previewable, and exportable in minutes
• Works with your tools: OGC API Features/Records, STAC API 1.0, direct tile URLs for QGIS, ArcGIS, and MapLibre
• Semantic and spatial search: pg_trgm fuzzy matching out of the box; add an embedding provider and enable semantic search to rank datasets by meaning (pgvector)
• Built-in map builder: compose multi-layer maps, style them, and share via public link or embeddable iframe
• AI-assisted (optional): chat with your maps, auto-generate descriptions, search by natural language. Bring an OpenAI-compatible endpoint or Anthropic key, or skip it entirely

See it in action

The examples below use a JWT bearer token. Mint one against the local stack (the login endpoint accepts an OAuth2 password form, so use -d with form fields, not JSON). Substitute your admin username and the password from .env (grep '^GEOLENS_ADMIN_PASSWORD=' .env):

TOKEN=$(curl -s -X POST http://localhost:8080/api/auth/login/ \
  -d 'username=admin&password=<your-admin-password>' | jq -r '.access_token')

Semantic search takes a one-time admin setup: an embedding provider and the AI + Semantic Search toggles in the admin AI settings, plus an embedding backfill for data ingested before setup (the search guide walks through it). Once that's on, search datasets by meaning instead of exact keyword matches:

# Semantic search ranks by meaning: "hydrology" surfaces subwatersheds, lakes,
# and river networks whose titles never mention the word
curl "http://localhost:8080/api/search/datasets/?q=hydrology&limit=3" \
  -H "Authorization: Bearer $TOKEN" | jq '.features[].properties.title'

Every dataset is also a standard OGC API Features endpoint:

# Grab a public collection id from the catalog. Search anonymously (no token) so
# the id is one anyone can read, matching the unauthenticated items request below.
CID=$(curl -s "http://localhost:8080/api/search/datasets/?q=countries&limit=1" \
  | jq -r '.features[0].id')

# GeoJSON features with a bbox filter, works in QGIS, ArcGIS, any OGC client
curl "http://localhost:8080/api/collections/$CID/items?bbox=-10,35,30,60&limit=5"

PostGIS and pgvector share one database, so with semantic search enabled you can rank datasets by meaning inside a spatial window in a single query. See the search guide for how semantic and spatial search work together.

Connect directly from QGIS: Layer > Add WFS / OGC API Features and point at http://localhost:8080/api/.

Features

Each example above has a full guide in the docs. What GeoLens reads, writes, and exposes:

Data ingestion and export

• Vector: Shapefile, GeoPackage, GeoJSON, CSV, XLSX
• Raster: GeoTIFF and Cloud-Optimized GeoTIFF (COG) with automatic conversion
• Mosaics: VRT-based raster mosaics from multiple source files
• Export: GeoJSON, Shapefile, GeoPackage, CSV, with CRS reprojection
• Provenance tracking and metadata editing

Standards and interop

• OGC API - Features and OGC API - Records; STAC API 1.0 catalog endpoint
• Direct tile URLs and per-user API keys for QGIS, ArcGIS, MapLibre, and any OGC client
• Vector tiles omit attribute columns below zoom 10 to keep low-zoom tiles small; add the cols=<column>,<column> query parameter to a tile URL to opt specific columns in at every zoom (names are validated against the dataset's columns, unknown names are dropped)
• JWT + OAuth 2.0/OIDC, RBAC with per-dataset permissions

Security

• JWT authentication with refresh tokens
• API key management per user
• OAuth 2.0 / OIDC support (Google, Microsoft, generic providers)
• Role-based access control (RBAC) with per-dataset permissions
• Self-serve registration is off by default; when enabled with SMTP verification, registration email delivery is uniform for new and colliding submissions
• Audit logging for all administrative actions
• Internationalization: English, Spanish, French, German

Screenshots

Find: search by meaning. A query for "natural disasters" surfaces earthquakes and volcanic eruptions with no keyword match, alongside type, location, and temporal filters

Inspect: every dataset gets a map preview, schema stats, and typed metadata. Here, 32,186 meteorite landings across the globe

Build: compose multi-layer maps in the browser with a drag-orderable layer stack and per-layer editors (here: the Matterhorn as a 3D terrain mesh from swissALTI3D lidar)

Ask AI: edit maps in natural language. "Label the volcanoes with their names" adds readable labels to the Restless Earth map (optional: bring an OpenAI-compatible endpoint or Anthropic key)

Quick start

Prerequisites: Docker Engine 24+ and Docker Compose v2. The bundled stack ships PostgreSQL 17. If you point GeoLens at an externally managed database, it must be PostgreSQL 13+ (for gen_random_uuid()) with pgvector 0.5+ (for HNSW semantic-search indexes), plus PostGIS, pg_trgm, and unaccent. The API and worker run in containers (Python 3.14 bundled, no host Python needed). The optional CLI runs on your host and requires Python 3.11+; the Python SDK and seed scripts require Python 3.10+.

The one-line install pulls the prebuilt, version-pinned images and starts the stack:

curl -fsSL https://getgeolens.com/install.sh | sh

Prefer to read the script or build from source first? Clone the repo and run the same installer. It builds the images locally instead of pulling them:

git clone https://github.com/geolens-io/geolens.git
cd geolens
bash scripts/install.sh

Either way, scripts/install.sh copies .env.example to .env, generates a JWT signing secret, sets up admin credentials, and runs docker compose up -d. The admin username defaults to admin; the admin password is auto-generated as a strong random value (written to .env, never printed to your terminal) unless you supply your own. For unattended installs, set GEOLENS_ADMIN_USERNAME and GEOLENS_ADMIN_PASSWORD in the environment before running and the prompts are skipped. Re-running the script is idempotent: existing values in .env are preserved.

Wait about 60 seconds for services to start, then open http://localhost:8080. Log in with your admin username and the generated password (retrieve it with grep '^GEOLENS_ADMIN_PASSWORD=' .env).

Verify all services are healthy:

docker compose ps

First-run notes: the one-line install pulls prebuilt images and is up in about a minute (only the small PostGIS + pgvector database layer builds locally). Cloning and running bash scripts/install.sh instead builds every image from source: 5-10 minutes on the first run (GDAL + Postgres extensions + the frontend bundle); subsequent starts settle in ~60 seconds either way. If ports 5434/8001/8080 are already taken, change DB_PORT, API_PORT, or FRONTEND_PORT in .env. For port conflicts, stuck startups, out-of-memory, and migration warnings, see the Troubleshooting guide.

For production deployment, see the Install Guide. A community-maintained Kubernetes Helm chart lives in the separate geolens-deployments repo.

Verify the installer

Each GitHub Release attaches a SHA256SUMS file generated by CI alongside install.sh. To confirm a downloaded installer was not tampered with before running it, download both assets from the same release and place them in the same directory, then run:

# Linux / Windows WSL
sha256sum -c SHA256SUMS

# macOS
shasum -a 256 -c SHA256SUMS

A passing check prints install.sh: OK.

Upgrading

To upgrade a prebuilt install, run ./scripts/upgrade.sh from your install directory. It backs up the database, pulls the new images, runs migrations behind a health gate, and prints a rollback recipe if anything fails. See UPGRADING.md for the prebuilt and source-build flows plus rollback, or the online Upgrade Guide.

Add your first dataset

The repo ships a small city-parks.geojson. Upload and publish it in one command with the GeoLens CLI:

pip install geolens-cli                              # installs the `geolens` command
geolens login http://localhost:8080/api              # use your admin username + password
geolens publish examples/manifests/first-catalog/city-parks.geojson --name "City Parks"

geolens publish runs the upload → preview → commit ingest flow and prints the new dataset's URL. One command takes a local file to a published, mappable dataset.

For repeatable, multi-dataset catalogs, describe your sources in a manifest (geolens.yaml) and apply it with geolens apply. Manifest sources are referenced by HTTP(S) URL, S3 URI, or a path already staged on the server; the examples in examples/manifests/ are templates to adapt. Scaffold a fresh one with geolens init and edit it for your sources:

geolens init                       # writes geolens.yaml in the current directory
geolens validate geolens.yaml      # local schema check, no API call
geolens apply geolens.yaml         # validates + applies via /ingest/manifest/apply

See the CLI guide for the full manifest schema, source kinds, and CI integration patterns.

Seed data

scripts/seed-showcase.py builds six showcase maps from public open data: a global tectonics story over real ocean-floor relief, the Manhattan 3D skyline colored by construction era (the hero above), 75 years of Atlantic hurricane tracks, clustered meteorite falls, the Matterhorn in 2 m lidar 3D terrain, and by-reference Sentinel-2 imagery of New York:

pip install httpx
python scripts/seed-showcase.py --username admin --password "$(grep '^GEOLENS_ADMIN_PASSWORD=' .env | cut -d= -f2-)"

Requires internet access to the upstream open-data sources. See scripts/README.md for flags (--no-terrain, --prune, …).

Architecture

GeoLens is a small set of services around a single PostgreSQL/PostGIS database: the API serves the catalog, search, and OGC/STAC endpoints; a worker handles ingestion; and Titiler serves raster tiles from object storage.

flowchart TB
    B["Browser: React + MapLibre app"]
    OGC["QGIS · ArcGIS · OGC/STAC clients"]

    NG["Nginx reverse proxy<br/>serves the React build, routes /api and tiles"]

    subgraph Application
      API["FastAPI<br/>catalog · semantic search · OGC/STAC · vector tiles"]
      W["Worker<br/>GDAL/ogr2ogr ingestion"]
      TT["Titiler<br/>COG raster tiles"]
    end

    subgraph store [Data and storage]
      PG[("PostgreSQL 17<br/>PostGIS · pgvector · pg_trgm<br/>+ Procrastinate queue")]
      OBJ[("Object storage<br/>local files or S3/MinIO")]
      CACHE[("Valkey cache")]
    end

    B --> NG
    OGC --> NG
    NG --> API
    NG --> TT
    API <--> PG
    API --> OBJ
    API -. tile/query cache .-> CACHE
    PG == job ==> W
    W --> PG
    W --> OBJ
    TT --> OBJ

Loading

Component	Technology
Frontend	React 19, Vite, MapLibre GL v5, TanStack Query, Tailwind CSS
Backend API	FastAPI (Python), GDAL/ogr2ogr, Procrastinate (task queue)
Raster Tiles	Titiler (COG tile server)
Object Storage	MinIO (S3-compatible, local dev) or any S3 provider
Cache	Valkey (tile and query cache)
Database	PostgreSQL 17 + PostGIS 3.5 + pgvector + pg_trgm (minimum: PostgreSQL 13, pgvector 0.5)
Reverse Proxy	Nginx (production) / Vite dev proxy (development)

Configuration

All configuration is managed through environment variables in .env. See the Configuration Reference for the full list of options with defaults and descriptions.

Connection pool budget

GeoLens ships tuned for a single PostgreSQL instance: the API, worker, and admin pools fit within 70 of 80 max_connections out of the box (Postgres max_connections is set to 80), sized by DB_POOL_SIZE (pool_size) and DB_MAX_OVERFLOW (max_overflow, default 3). See Connection Pool Tuning for the per-process budget and how to raise the ceiling.

Backups

Automated, scheduled backups run by default. You do not need a --profile backup flag. The backup service starts alongside api, worker, and db on every docker compose up and runs pg_dump on a daily/weekly schedule alongside an archive of the object-storage staging volume, so a restore reproduces a working instance (DB + uploaded files).

Off-site (S3) upload is additionally gated on BACKUP_S3_ENABLED=true. The built-in uploader signs requests with AWS Signature V4 (awscli), compatible with Cloudflare R2, modern AWS S3, and MinIO. A failed upload surfaces a visible ERROR in container logs (not a swallowed warning), so silent offsite backup loss is detectable immediately.

For day-2 operations, restore procedures, and incident response, see RUNBOOK.md. For provider-specific configuration options, see Backups & Restore.

Monitoring

The API and worker export Prometheus metrics out of the box (HTTP rate/latency/ errors, job-queue depth, DB pool, tile-cache). Reference scrape config, alert rules, and a Grafana dashboard ship in infra/monitoring/; see RUNBOOK.md §4 for the setup steps.

Reference

Guide	Description
Install Guide	Step-by-step deployment with Docker Compose
Upgrade Guide	Upgrading between versions with rollback procedures
Configuration Reference	All environment variables and their defaults
Admin Guide	User management, datasets, system health
Self-host on AWS, GCP, or DigitalOcean	Managed database, object storage, and cache deployment guides
CLI & Manifests	Publish files and manage catalogs with the geolens CLI
API Reference	Auto-generated reference at docs.getgeolens.com; interactive Swagger UI at /api/docs when running
Manifest examples	Template geolens.yaml manifests to adapt: public-cog (remote COG), url-source, s3-source, publication-states

Community

• GitHub Discussions: questions, ideas, show and tell
• Support: where to ask for help and how problems get routed
• Contributing Guide: development setup, code style, and PR guidelines

Known limitations

• Single PostgreSQL instance, with no built-in high availability or clustering.
• GeoLens is designed for one organization per self-hosted deployment.
• Terrain rendering assumes DEM units are in meters; datasets in other vertical units may render exaggerated.
• The self-hosted distribution is young and some features and APIs may still change (see the Early release note above).

License

GeoLens is licensed under the Apache License 2.0. The GeoLens name, logo, and brand assets are not covered by this license. See TRADEMARKS.md. Third-party sample-data attribution is in THIRD_PARTY_DATA.md.

Project policies: governance · maintainers · contributing · security · release process · egress & air-gap.