Move MQTT Data Where It Needs to Go. Without a Second Stack.
Pro Mosquitto bridges stream MQTT messages directly to Postgres, Snowflake, Kafka, and 18 other targets. They run as plugins in the broker. Nothing extra to deploy or scale. No glue code to maintain.
MQTT sources
Pro Mosquitto
Broker + Bridges
In-broker plugins
Postgres
Snowflake
Kafka+ many more
Targets
PostgresSnowflakeKafka
InfluxDBMost MQTT Integrations Start as a Script. Then They Grow.
Every additional target adds another component to deploy, monitor, and restart. The operational shape is the same whether the starting tool was a custom script, Node-RED, or an ETL connector.
The quick fix
A script moves one MQTT stream
The typical path: someone writes a Python or Node.js service that subscribes to MQTT and writes to Postgres. It works.
The hidden cost
Every target becomes another thing to run
Six months later there are three targets, a Node-RED flow for monitoring, retry logic that mostly works, and a runbook for restarting things in the right order.
The simpler shape
Bridges run where MQTT already lives
Pro Mosquitto integrations run as plugins inside the broker process itself. Each bridge has its own queue.
Integrations as Broker Plugins
Cedalo bridges are plugins that run in the same container as Pro Mosquitto. Nothing extra to deploy alongside the broker - and each bridge has its own queue so the broker keeps ingesting when a target slows down.
In-broker bridges
5 active · each with its own queue
In-Broker Plugins
Bridges run as plugins in the same container as the broker. No sidecar containers or separate connector cluster to operate.
Queue per Bridge
When a target slows or goes offline, messages buffer in a queue. The broker keeps ingesting; the bridge resumes when the target is back.
Configured in Cedalo MQTT Platform
Add, edit, and monitor integrations through the same UI as the broker. No connector-specific YAML or deployment pipeline.
Edge to Cloud
The same architecture runs on edge hardware next to a PLC and on the Kubernetes cluster running your analytics platform.
Common Integration Patterns
Four common patterns and the bridges that handle them. Start with the outcome, then pick the target systems that match your stack.
Time-Series Historian
Stream sensor and process data to a time-series store for monitoring, trending, and anomaly detection.
Data Warehouse & Analytics
Land MQTT data in cloud warehouses for BI, reporting, and ML pipelines without intermediate ETL services.
Streaming Backbone
Bridge MQTT into existing event-streaming infrastructure for fan-out, replay, or feeding downstream services.
Operational Database
Write MQTT messages directly to relational and document databases for transactional, application, and reporting workflows.
All Integrations
21+ bridges and exporters, ready to deploy. Filter by use case or technology category.
PostgreSQL Bridge
Persist MQTT messages to PostgreSQL for application backends, reporting, and operational workflows.
Snowflake Bridge
Stream MQTT data into Snowflake for BI, analytics, and downstream ML pipelines.
Kafka Bridge
Forward MQTT topics to Apache Kafka for fan-out and integration with existing streaming infrastructure.
InfluxDB Bridge
Stream sensor data to InfluxDB for time-series monitoring, trending, and anomaly detection.
InfluxDB Metrics Exporter
Export broker performance and operational metrics to InfluxDB for monitoring dashboards.
MongoDB Bridge
Persist MQTT messages to MongoDB for document-based application storage.
MongoDB Atlas Bridge
Stream MQTT data to MongoDB Atlas managed cloud database.
TimescaleDB Bridge
Stream time-series MQTT data to TimescaleDB for high-volume sensor workloads.
Amazon Redshift Bridge
Stream MQTT data to Amazon Redshift for warehouse-scale analytics.
Databricks Bridge
Stream MQTT data into Databricks for lakehouse analytics, BI, and ML pipelines.
Azure EventHub Bridge
Forward MQTT messages to Azure Event Hubs for Microsoft cloud event pipelines.
Google Pub/Sub Bridge
Bridge MQTT topics to Google Cloud Pub/Sub for GCP-based event pipelines.
Microsoft SQL Server Bridge
Write MQTT messages to Microsoft SQL Server for enterprise application backends.
MySQL Bridge
Persist MQTT data to MySQL for application storage and reporting.
MariaDB Bridge
Stream MQTT messages to MariaDB for open-source SQL workloads.
Oracle DB Bridge
Integrate MQTT data with Oracle Database for enterprise transactional systems.
CockroachDB Bridge
Stream MQTT data to CockroachDB distributed SQL for resilient global deployments.
Google AlloyDB Bridge
Connect MQTT data to Google AlloyDB, PostgreSQL-compatible managed cloud database.
MQTT Bridge
Bridge between MQTT brokers for multi-site, multi-region, and hybrid edge-cloud topologies.
HTTP Bridge
Forward MQTT messages to HTTP endpoints for REST API and webhook integration.
Prometheus Metrics Exporter
Export broker metrics in Prometheus format for Grafana dashboards and alerting.
Bridge: streams MQTT messages to and from a target system. Exporter: exports broker operational metrics to a monitoring system.
Don't See Your Target System?
We extend the bridge catalog regularly. If your target system isn't here yet, get in touch and tell us what you're integrating.
How it works
- 1
Tell us about your target system and use case
- 2
We evaluate the fit and scope the work
- 3
We build and support the bridge with the same SLA as our shipped bridges
Where Cedalo bridges run in industrial deployments.
Teams ship MQTT data through Pro Mosquitto to warehouses, time-series stores, and streaming platforms - without maintaining a second integration tier.
Frequently Asked Questions
Common questions about how bridges run inside the broker, what happens when targets fail, and what's included per tier.
Run your MQTT integrations as part of the broker.
Try Pro Mosquitto with the bridges your stack needs, or talk to us about something custom.