The wire-protocol bridge from Databricks to your GIS stack.

Platbridge replaces PostGIS, FME, and your spatial ETL pipelines with a single bridge that speaks PostgreSQL on the front and Databricks SQL on the back. ArcGIS Pro, GeoServer, QGIS — every PostGIS-compatible tool — connects unchanged.

Architecture

One bridge instead of an intermediate spatial tier.

Today, viewing Databricks data in a GIS requires ETLing it into PostGIS or SDE first. Platbridge eliminates that tier — the GIS connects directly to Databricks over the PostgreSQL wire protocol.

TODAYDatabricksLakehouseETLPostGIS / SDEIntermediate tierQueryArcGIS / GeoServerPresentationWITH PLATBRIDGEDatabricksLakehousePostgreSQL wirePlatbridgeNo intermediate storagePostGIS protocolArcGIS / GeoServerPresentation

The platform

One bridge, three things it does well.

Wire-protocol translation, spatial acceleration, and catalog-aware governance — engineered together as a single product.

PostgreSQL ↔ Databricks SQL

Every PostGIS tool already works.

Platbridge speaks the PostgreSQL wire protocol on the front and Databricks SQL on the back. There is no SDK to integrate, no API client to maintain, no plugin to install in your GIS. ArcGIS Pro, ArcGIS Enterprise, GeoServer, QGIS, FME — every tool that connects to PostGIS today connects to Platbridge unchanged.

PostgreSQL 14+ wire protocol

Standard libpq, JDBC, ODBC clients all connect. SSL/TLS, SCRAM authentication.

PostGIS function coverage

ST_Intersects, ST_Within, ST_Buffer, ST_Transform, and the wider analytic surface that GIS tools issue.

Cursor-aware result streaming

Large viewport queries stream incrementally — no loading the whole layer into memory.

One bridge. Two deployment paths.

The same Platbridge runtime, two installation flavors. Start where your infrastructure lives.

Kubernetes

Helm chart
  • helm install one-liner
  • AKS, EKS, GKE, Hetzner, on-prem
  • Horizontal pod autoscaling
  • Standard k8s observability
Helm install snippet

Linux

systemd
  • Single binary, no runtime deps
  • systemd unit included
  • RHEL, Ubuntu, Debian, SUSE
  • Air-gapped deployment supported
Linux install steps

Three steps to a connected GIS.

Install. Configure. Connect.

1

Install Platbridge

Drop it into your existing Kubernetes cluster with one Helm command.

helm repo add platbridge https://charts.platbridge.io
helm install platbridge platbridge/platbridge
2

Configure your Databricks workspace

Point Platbridge at the catalog you want to expose. Permissions and lineage flow through.

[databricks]
host = "adb-1234567890.azuredatabricks.net"
catalog = "production_spatial"
token_secret_ref = "platbridge/databricks-token"
3

Connect from ArcGIS Pro or GeoServer

Use a standard PostGIS connection string. The GIS tool never knows it's not talking to PostGIS.

host: platbridge.your-domain.local
port: 5432
database: production_spatial
user: <your-databricks-user>

The architecture gets simpler. Not more complex.

Most data-integration products add a component to deploy, monitor, secure, and scale. Platbridge does the opposite. Customers replace a stack of infrastructure with a single bridge.

×
PostGIS instances
No parallel spatial database to operate.
×
FME servers
No transformation servers to license and run.
×
ETL pipelines
No scheduled jobs to author, monitor, and fix.
×
Sync processes
No replication windows or refresh delays.
×
Duplicate storage
No paying twice for the same dataset.
×
Split governance
No reconciling permissions across two systems.

The engine

Powered by platdb — our patent-pending spatial database engine.

Bridging a data lake to a GIS stack at wire speed isn't something you bolt onto an off-the-shelf connector. Platbridge runs on platdb — columnar geometry in Parquet, H3 hierarchical hexagonal indexing, row-group R-tree pruning, and SIMD-accelerated geometry operations.

Learn more about platdb

Wherever Databricks meets a GIS stack.

Four scenarios where Platbridge is already in trial or pilot.

Energy

A petroleum engineer maps real-time drilling telemetry against historical wellbore trajectories — both layers served live from the same Databricks lakehouse.

Utilities

A distribution operator visualizes outage events against the live asset hierarchy during storm response — Databricks data updates every five minutes, visible immediately.

Government

A state geological survey publishes hazard maps through GeoServer with Databricks as the authoritative data tier.

Environmental

A climate monitoring program correlates sensor telemetry with satellite imagery in ArcGIS Pro, both streams direct from Databricks.

Simple pricing. Scales with your usage.

Annual subscription. You pay for the bridge software; Databricks costs are paid separately to Databricks.

Starter

Getting started

For teams onboarding a single Databricks catalog with a small group of GIS users.

  • Single Databricks catalog
  • Community support
  • Standard SLA
  • Helm or Linux install
Contact sales

Professional

Production workloads

For mid-sized GIS programs running across multiple catalogs and analyst teams.

  • Multiple Databricks catalogs
  • Production support
  • Production SLA
  • Priority issue response
Contact sales

Enterprise

Large organizations

For organization-wide deployments across every catalog, every team, every region.

  • Unlimited Databricks catalogs
  • 24/7 support + dedicated CSM
  • Custom SLA
  • On-prem and air-gapped options
Contact sales

Contact sales for a quote tailored to your environment.

Frequently asked questions

What enterprise teams ask before a Platbridge trial.

Get started with Platbridge

One bridge, three ways to install. Full deployment guide in the docs.

Helm (Kubernetes)

helm repo add platbridge \
  https://charts.platbridge.io
helm install platbridge \
  platbridge/platbridge

Linux (systemd)

# Single binary
curl -L https://platbridge.io/dl/latest \
  -o platbridge
sudo install platbridge /usr/local/bin/

Docker (testing)

docker run -p 5432:5432 \
  geopointlabs/platbridge:latest

See it on your own data.

A 30-minute call. We'll show Platbridge connected to a sample Databricks workspace and discuss what a trial on your environment would look like.