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However, on-prem databases are slow, rigid, and expensive to maintain, limiting the speed at which businesses can scale and drive innovation. Today’s organizations need scalable, cloud-native databases with real-time data. This demo walks you through building streaming data pipelines with Confluent Cloud. You’ll learn about:\n\n- Confluent’s fully managed source connectors to stream customer data and credit card transactions in real time into Confluent Cloud\n- Process and enrich data streams in real time. You'll use aggregates and windowing to create a customer list of potentially stolen credit cards\n- A fully managed sink connector to load enriched data into MongoDB Atlas for real-time fraud analysis\n\nBreak down data silos and stream on-premises, hybrid, and multicloud data to cloud databases such as MongoDB Atlas, Azure Cosmos DB and more, so that every system and application has a consistent, up-to-date, and enhanced view of the data at all times. With Confluent streaming data pipelines, you can connect, process, and govern real-time data for all of your databases. Unlock real-time insights, focus on building innovative apps instead of managing databases, and confidently pave a path to cloud migration and transformation.\n\nTo learn more about Confluent’s solution, visit the [Database streaming pipelines page](https://www.confluent.io/use-case/database)\n\nThere are two versions of this demo\n\n1. Using [ksqlDB](./streaming-data-pipelines-with-ksqlDB/) as the stream processing engine.\n   - In this version there are two source connectors (Oracle CDC and RabbitMQ)\n   - Oracle database contains customers information\n   - RabbitMQ contains each customer's credit card transactions\n   \u003cdiv align=\"center\"\u003e \n    \u003cimg src=\"./streaming-data-pipelines-with-ksqlDB/images/arch_diagram.png\" width =100% heigth=100%\u003e\n     \u003c/div\u003e\n1. 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