Easily build robust, reactive data pipelines that stream events between applications and services in real time.
Why MongoDB and Apache Kafka?
MongoDB and Kafka are at the heart of modern data architectures. Kafka is designed for boundless streams of data that sequentially write events into commit logs, allowing real-time data movement between your services.
Configure as a Sink
Map and persist events from Kafka topics directly to MongoDB collections with ease. Ingest events from your Kakfa topics directly into MongoDB collections, exposing the data to your services for efficient querying, enrichment, and analytics.
Configure as a Source
Publish data changes from MongoDB into Kafka topics for streaming to consuming apps. Data is captured via Change Streams within the MongoDB cluster and published into Kafka topics. This enables consuming apps to react to data changes in real time using an event-driven programming style.
MongoDB customers have experienced success with the Kafka Connector across a span of industries and companies for a variety of use cases.
ao.com, a leading online electrical retailer, uses Kafka to push all data changes from its source databases to MongoDB Atlas. This creates a single source of truth for all customer data to drive new and enhanced applications and business processes including customer service, fraud detection, and GDPR compliance. Employees with appropriate permissions can access customer data from one easy-to-consume operational data layer.
comparethemarket.com, a leading price comparison provider, uses MongoDB as the default operational database across its microservices architecture. While each microservice uses its own MongoDB database, the company needs to maintain synchronization between services, so every application event is written to a Kafka topic. Relevant events are written to MongoDB to enable real-time personalization and optimize the customer experience.
State, an intelligent opinion network connecting people with similar beliefs, writes survey data to MongoDB and leverages MongoDB Change Streams to push database changes into Kafka topics where they are consumed by its user recommendation engine. This engine suggests potentially interesting users and updates instantly as soon as a user contributes a new opinion.