Deploy Coreflux MQTT Broker with Managed Databases

You integrate Coreflux MQTT broker with a managed database by defining a Route in LoT that points to your target service (PostgreSQL, MySQL, MongoDB, or OpenSearch). Each route uses the appropriate connection parameters (server or connection string, port, database name, username, password, and SSL/TLS options) and automatically persists MQTT message payloads into tables, collections, or indexes. Once the route is defined, you attach it to a Model with the STORE IN directive so that every processed message is written to your chosen database.

Yes. Coreflux is designed as a low-code integration layer, so you do not need to write application code or external ETL jobs to persist data. For each database type, you configure a LoT route (for example, PostgreSQL_Log, MySQL_Log, mongo_route, or OpenSearch_Log) and then extend your model with STORE IN "<route_name>" WITH TABLE "MachineProductionData". Coreflux handles connection pooling, retries, and error handling, so you focus on modeling topics and transformations instead of boilerplate database code.

The best managed database for your MQTT IoT data depends on your data structure, query needs, and analytics goals. Use the below comparison table below to help you decide:

Tip: You can use more than one managed database at the same time by configuring multiple Coreflux routes. This makes it possible to store structured IoT data in PostgreSQL or MySQL, aggregate logs and metrics in OpenSearch, and collect unstructured or schemaless data in MongoDB, all from the same MQTT stream.

Coreflux keeps all processed values available on MQTT topics for real-time consumption, dashboards, or additional pipelines, while Routes persist the same modeled data to your databases for historical queries. In practice, you can subscribe to topics for immediate reactions (alerts, control loops) and query PostgreSQL/MySQL/MongoDB/OpenSearch for aggregates, trends, and long-term analysis. This dual-path design mirrors common patterns in MQTT and IoT data integration guides, where a broker provides live messaging and databases provide durable storage and analytics.

When deploying on the cloud provider, you can use VPC networking to keep all communication between your Coreflux MQTT broker and databases private. The VPC isolates your resources from public internet access, and managed databases support TLS encryption for connections. Additionally, you can create dedicated database users with limited permissions for your Coreflux application, following the principle of least privilege.

Yes. This architecture mirrors patterns used in production MQTT and database integrations, where a broker front-ends device traffic and a managed database tier provides durability and analytics. managed databases offer automated backups, high availability, and monitoring, while Coreflux MQTT broker can scale horizontally to handle high message throughput. For production, you should also configure firewall rules, use strong credentials, enable TLS for MQTT and database connections, and size your droplets and clusters based on expected message volume.

Yes. MQTT brokers are often deployed in private networks or edge environments, and public resources consistently note that MQTT can work without the public internet as long as clients can reach the broker. With the cloud provider, you can keep Coreflux and your databases inside a VPC and only expose what is strictly necessary (for example, a VPN, bastion host, or limited firewall rules). You can also synchronize selected topics with other brokers or cloud regions if you need hybrid or multi-site architectures.

MQTT is optimized for lightweight, event-driven messaging; databases are optimized for storage and querying. Storing every raw message can become expensive or noisy, so best practices recommend modeling data carefully (for example, aggregating metrics, filtering topics, or downsampling). Very low-power devices or ultra-constrained networks might struggle with persistent connections or TLS overhead, in which case you may need to tune QoS levels, batching, and retention policies. As long as you design your models and routes with these trade-offs in mind, MQTT plus managed databases works well for most IoT scenarios.

You should choose a managed database based on your IoT data structure, scalability, and how you want to query your device data. The table below summarizes the strengths of each option: