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Ingest MQTT Data into MongoDB


EMQX Enterprise Edition features. EMQX Enterprise Edition provides comprehensive coverage of key business scenarios, rich data integration, product-level reliability, and 24/7 global technical support. Experience the benefits of this enterprise-ready MQTT messaging platform today.

MongoDB, a leading NoSQL database, is renowned for its flexibility in schema design, scalability, and capacity to store large volumes of structured and semi-structured data. By integrating EMQX with MongoDB, users can efficiently ingest MQTT messages and client events directly into MongoDB. This facilitates long-term series data storage and advanced querying capabilities within MongoDB. The integration ensures a single-directional flow, where MQTT messages from EMQX are written into the MongoDB database. This powerful combination is a solid foundation for businesses looking to manage their IoT data effectively.

This page provides a comprehensive introduction to the data integration between EMQX and MongoDB with practical instructions on creating a rule and data bridge.

How It Works

MongoDB data integration is an out-of-the-box feature in EMQX designed to bridge the gap between MQTT-based IoT data and MongoDB's powerful data storage capabilities. With a built-in rule engine component, the integration simplifies the process of ingesting data from EMQX to MongoDB for storage and management, eliminating the need for complex coding.

The diagram below illustrates a typical architecture of data integration between EMQX and MongoDB.


Ingesting MQTT data into MongoDB works as follows:

  1. Message publication and reception: IoT devices, whether they are part of connected vehicles, IIoT systems, or energy management platforms, establish successful connections to EMQX through the MQTT protocol and publish MQTT messages to specific topics. When EMQX receives these messages, it initiates the matching process within its rules engine.
  2. Message data processing: When a message arrives, it passes through the rule engine and is then processed by the rule defined in EMQX. The rules, based on predefined criteria, determine which messages need to be routed to MongoDB. If any rules specify payload transformations, those transformations are applied, such as converting data formats, filtering out specific information, or enriching the payload with additional context.
  3. Data ingestion into MongoDB: Once the rule engine identifies a message for MongoDB storage, it triggers an action of forwarding the messages to MongoDB. Processed data will be seamlessly written into the collection of the MongoDB database.
  4. Data storage and utilization: With the data now stored in MongoDB, businesses can harness its querying power for various use cases. For instance, in the realm of connected vehicles, this stored data can inform fleet management systems about vehicle health, optimize route planning based on real-time metrics, or track assets. Similarly, in IIoT settings, the data might be used to monitor machinery health, forecast maintenance, or optimize production schedules.

By using this integrated system, businesses in sectors like power and energy can continuously monitor grid health, forecast demand, or identify potential outages before they happen. The value derived from the real-time and historical data not only ensures operational efficiency but can also lead to significant cost savings and enhanced customer experiences.

Features and Benefits

The data integration with MongoDB offers a range of features and benefits tailored to ensure effective data handling and storage:

  • Streamlined IoT Data Management

    You can ingest, store, process, and analyze your IoT data all in one place, eliminating the need for complicated integrations and tedious data migrations. Say goodbye to data silos and hello to a unified view of your IoT data.

  • Real-time Data Processing

    EMQX is built for handling real-time data streams, ensuring efficient and reliable data transmission from source systems to MongoDB. It enables organizations to capture and analyze data in real-time, making it ideal for use cases requiring immediate insights and actions.

  • Flexible MongoDB Connection Options

    Whether you operate with a single MongoDB instance or leverage the robustness of a replica set, the bridge offers native support to connect with both configurations, providing businesses with the flexibility to adapt as per their infrastructure needs.

  • High Performance and Scalability

    EMQX's distributed architecture and MongoDB's columnar storage format enable seamless scalability as data volumes increase. This ensures consistent performance and responsiveness, even with large datasets. As your IoT deployments grow, your data storage capabilities can scale with ease.

  • Flexible Data Transformation

    EMQX provides a powerful SQL-based Rule Engine, allowing organizations to pre-process data before storing it in MongoDB. It supports various data transformation mechanisms, such as filtering, routing, aggregation, and enrichment, enabling organizations to shape the data according to their needs.

  • NoSQL

    MongoDB's schema-less architecture ensures that diverse MQTT message structures can be easily stored without the need for rigid schemas, accommodating the dynamic nature of IoT data.

  • Reliable Data Storage

    Once the EMQX rule engine processes and routes the message, it is stored in MongoDB with the platform's proven reliability, ensuring data integrity and consistent availability.

  • Operational Metrics and Advanced Analytics

    Glean insights from metrics such as the total message count, egress traffic rate, and more. These metrics, combined with MongoDB's powerful querying, can be utilized to monitor, analyze, and optimize the data flow, empowering users to gain valuable insights from IoT data, enabling predictive analytics, anomaly detection, and more.

  • Latest MongoDB Version Support

    The bridge is compatible with and supports the latest versions of MongoDB, ensuring users benefit from the newest features, optimizations, and security updates offered by the database platform.

  • Cost-Effective

    EMQX and MongoDB are both open-source solutions, meaning they are cost-effective compared to proprietary solutions. This can help reduce the total cost of ownership and improve the return on investment for IoT projects.

This MongoDB integration fortifies your IoT infrastructure, ensuring that vast amounts of data generated by your devices are not just stored but are also ready for future querying and analysis. The ease of setup and operational excellence it brings can greatly enhance the efficiency and reliability of your IoT systems.

Before You Start

This section describes the preparations you need to complete before you start to create the MongoDB data bridges in EMQX Dashboard.


Set Up MongoDB Server

You can use the following commands to install MongoDB via Docker, run the docker image, and create a user.

#  To start the MongoDB docker image and set the password as public
docker run -d --name mongodb -p 27017:27017 mongo

# Access the container
docker exec -it mongodb bash

# Locate the MongoDB server in the container

# Create a user
use admin
db.createUser({ user: "admin", pwd: "public", roles: [ { role: "root", db: "admin" } ] })

Create a Database

You can use the following command to create a database and collection in MongoDB.

# Create database emqx_data
use emqx_data

# create collection emqx_messages

Create Rule and MongoDB Data Bridge

  1. Go to EMQX Dashboard, and click Integration -> Rules.

  2. Click Create on the top right corner of the page.

  3. Input my_rule as the rule ID, and set the rules in the SQL Editor. If you want to save the MQTT messages under topic t/# to MongoDB, you can use the SQL syntax below.

    Note: If you want to specify your own SQL syntax, ensure you have included all fields required by the data bridge in the SELECT part.


    For example, you can use the SQL syntax below to save timestamp as data type and the payload in JSON as JSON strings:

      mongo_date(timestamp) as timestamp,
      json_encode(payload) as payload

    Note: If you are a beginner user, click SQL Examples and Enable Test to learn and test the SQL rule.

  4. Click the + Add Action button to define an action that will be triggered by the rule. Select Forwarding with Data Bridge from the dropdown list. With this action, EMQX sends the data processed by the rule to MongoDB.

  5. Click the + icon next to the Data bridge drop-down box to create a data bridge.

  6. Select MongoDB from the Type of Data Bridge drop-down list.

  7. Enter a name for the data bridge. The name should be a combination of upper/lower case letters and numbers.

  8. Configure the MongoDB server connection information. Fill in the required fields (marked with an asterisk).

    • MongoDB Mode: Select the type of MongoDB deployment you are connecting to based on your actual deployment mode. In this demonstration, you can select single for example.
      • single: a single standalone MongoDB instance.
      • rs: Replica Set, a group of mongod processes that maintain the same data set.
      • sharded: a sharded cluster in MongoDB.
    • Srv Record: Disabled by default. Once enabled, it allows EMQX to use DNS SRV records to discover the MongoDB hosts it should connect to, which makes it easier to connect to replica sets or sharded clusters without having to specify each host in the connection string.
    • Server Host: Enter, or the actual URL if the MongoDB server is running remotely.
    • Database Name: Enter emqx_data.
    • Collection: Enter emqx_messages.
    • Configure the other options according to your business needs.
    • If you want to establish an encrypted connection, click the Enable TLS toggle switch. For more information about TLS connection, see TLS for External Resource Access.
  9. Configure the Payload template to save clientid, topic, qos, timestamp, and payload to MongoDB. This template will be executed via the MongoDB insert command, and the sample code is as follows:

      "clientid": "${clientid}",
      "topic": "${topic}",
      "qos": ${qos},
      "timestamp": ${timestamp},
      "payload": ${payload}

    When configuring the payload template, pay attention to the following:

    • All keys need to be wrapped in double quotes ";

    • Auto-derivation of the data type of "value" is not supported:

      • Characters need to be wrapped with ", otherwise, an error will be reported;
      • Values do not need to be wrapped, otherwise, they will be recognized as characters;
      • For timestamp, date, and time types, if no special treatment is performed, they will be recognized as numeric or character types. To store them as date or time, use the mongo_date function in the rule SQL to process the fields. For details, see Time and date functions.
    • Nested objects are allowed, when value is a JSON object:

      • It is not allowed to use " to nest the value in the template, otherwise, it will cause an execution error;
      • Objects will be nested and stored according to their own structure;
    • To store objects as JSON characters, use the json_encode function in rule SQL for the conversion, and the corresponding value in the template is still not allowed to be wrapped with ".

  10. Click the Add button to complete the data bridge configuration. You will be redirected back to the Add Action page. Select the MongoDB Data Bridge you just created from the Data bridge drop-down list. Click the Add button at the bottom to include this action in the rule.

  11. Back on the Create Rule page, verify the configured information. Click the Create button to generate the rule.

Now you have successfully created the rule and data bridge. You can click Integration -> Flows to view the topology. It can be seen that the messages under topic t/# are sent and saved to MongoDB after parsing by rule my_rule.

Test MongoDB Data Bridge and Rule

To test if the MongoDB data bridge and rule work as you expected, you can use the MQTTX to simulate a client to publish MQTT messages to EMQX.

  1. Use MQTTX to send a message to topic t/1:

    mqttx pub -i emqx_c -t t/1 -m '{ "msg": "hello MongoDB" }'
  2. Click the name of the data bridge on the Data Bridge page to view the statistics. Check the running status of the two data bridges, there should be one new Matched and one new Sent Successfully message.

  3. Check whether the message is written into collection emqx_messages:

    > db.emqx_messages.find().pretty()
        "_id" : ObjectId("63db7059df489d01ed000009"),
        "clientid" : "emqx_c",
        "payload" : {
          "msg" : "hello MongoDB"
        "qos" : 0,
        "timestamp" : NumberLong("1675325529070"),
        "topic" : "t/1"

    If you use the second SQL syntax in rule configuration, the returned information should be:

    > db.emqx_messages.find().pretty()
        "_id" : ObjectId("63db7535df489d01ed000013"),
        "clientid" : "emqx_c",
        "payload" : "{ \"msg\": \"hello MongoDB\" }",
        "qos" : 0,
        "timestamp" : ISODate("2023-02-02T08:33:36.715Z"),
        "topic" : "t/1"

Advanced Configurations

This section delves deeper into the advanced configuration options available for the EMQX MongoDB data bridge. When configuring the data bridge, navigate to Advanced Settings to tailor the following parameters to meet your specific needs.

FieldsDescriptionsRecommended Value
Connect TimeoutThe time duration EMQX will wait while attempting to establish a connection to MongoDB before timing out.30s
Socket TimeoutThis determines how long EMQX will wait while trying to send or receive data on a socket connection with MongoDB before it times out.30s
Max Overflow WorkersSpecifies the additional number of workers that can be created when all existing workers are occupied. This setting is crucial in times of workload surges to permit more concurrent connections to MongoDB.0
Wait Queue TimeoutThe maximum duration a worker can remain idle while waiting for a connection to MongoDB to become available.10s
Heartbeat PeriodDefines the interval at which the driver checks the state of the MongoDB deployment. This specifies the time between consecutive checks, effectively controlling the frequency of these heartbeat signals to ensure MongoDB's operational status.200s
Minimum Heartbeat PeriodSets the shortest time interval allowed between heartbeats, ensuring that the driver doesn't check the MongoDB state too frequently. This is vital for avoiding unnecessary loads and ensuring efficient communication between EMQX and MongoDB.200s
Use Legacy ProtocolDetermines if MongoDB's legacy communication protocol should be used. MongoDB introduced a new wire protocol in version 3.6, with the legacy protocol retained for backward compatibility. This setting can be set to true, false, or auto. In "auto" mode (default option), EMQX will automatically determine which protocol to use based on the detected MongoDB

More Information

Check out the following links to learn more:


Storing Messages to MongoDB Database | EMQX Rule Engine Series


MQTT Performance Benchmark Testing: EMQX-MongoDB Integration