Debezium vs Slick: What are the differences?

# Introduction
This Markdown code explains the key differences between Debezium and Slick.

1. **Data Change Capture**:
Debezium is specialized in capturing changes in databases and streaming them to other systems, whereas Slick is best suited for ORM (Object-Relational Mapping) operations and database interactions within applications.

2. **Use Case**:
Debezium is commonly used for real-time data streaming, especially in scenarios where capturing data changes is crucial for analytics and reporting. On the other hand, Slick is more focused on simplifying database interactions and providing a seamless way to work with databases in Scala applications.

3. **Technology Stack**:
Debezium is built on top of Apache Kafka, providing scalability and fault tolerance for real-time streaming of database changes. In contrast, Slick is built as a library for Scala to interact with SQL databases, offering a functional and type-safe approach to working with databases.

4. **Programming Paradigm**:
Debezium follows the concept of change data capture (CDC), enabling applications to react to database changes instantly, whereas Slick emphasizes a more traditional ORM approach, mapping database tables to objects in the application code.

5. **Maintenance Overhead**:
Debezium requires managing Kafka clusters for reliable data streaming and monitoring, adding complexity in deployment and maintenance. In comparison, Slick does not have dependencies on external platforms like Kafka, reducing the operational overhead on the infrastructure side.

6. **Community and Ecosystem**:
Debezium has a vibrant community around real-time data streaming and database integration, offering extensive support and resources for users. Slick, being more focused on database operations within applications, has a smaller community but provides specific solutions for ORM needs in Scala projects.

In Summary, Debezium excels in real-time data change capture and streaming using Apache Kafka, while Slick is more suited for ORM operations and database interactions within Scala applications.