Set up a Kafka integration for Public Cloud Databases for MongoDB

Introduction

The MongoDB Kafka Connector is an integration tool that bridges MongoDB with Apache Kafka, enabling real-time data synchronization and streaming between the two platforms. This connector facilitates the seamless transfer of data, allowing MongoDB to be used both as a source and a sink within a Kafka ecosystem. By leveraging this connector, developers can build robust data pipelines, ensuring efficient and reliable data flow across their applications.

Quick Start Guide

Learn how to get started with the MongoDB Kafka Connector and begin working with data in the Kafka Connector Quick Start section.

Tutorials

Follow tutorials to learn how to set up the MongoDB Kafka Connector to read and write data for several use cases.

Key Components

1. Source Connector: Captures changes from MongoDB and streams them into Kafka topics. It uses MongoDB’s Change Streams to monitor changes in collections and databases.
2. Sink Connector: Reads data from Kafka topics and writes it into MongoDB collections. This component ensures that data from various Kafka topics can be persisted in MongoDB for further processing or querying.

Setup Kafka Sink and Source Connectors

Step 1: Create KafkaConnect and Kafka services

Under Data Streaming create KafkaConnect and Kafka services.

Step 2: Integrate the Kafka service to KafkaConnect

Select the Kafka Connect service and under Service Integration, click the + Add an Integration button and select KafkaConnect as integration type, an then add the Kafka service.

Step 3: Add the Connector

Under Connectors tab in KafkaConnect, click the + Add a Connector and then select either MongoDB Kafka Sink Connector or MongoDB Kafka Source Connector.

Step 4: Configure the Connector

You can refer to Sink Connector Configuration Properties and Source Connector Configuration Properties to complete the setup.

Monitoring

Learn how to monitor your MongoDB Kafka source and sink connectors in the Monitoring section.

Troubleshooting

Learn how to resolve issues you may encounter while running the MongoDB Kafka Connector in the Troubleshooting section.

Use Cases

• Data Streaming: Real-time data streaming from MongoDB to Kafka for analytics and monitoring.
• ETL Pipelines: Using Kafka as a central hub for ETL processes, with MongoDB serving as a source or sink.
• Microservices Integration: Synchronizing data across microservices architectures, ensuring consistent data states.
• Event-Driven Architectures: Building event-driven systems where MongoDB and Kafka work together to handle events and triggers efficiently.

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