KSQL vs riko: What are the differences?

# Key Differences Between KSQL and riko

<Write Introduction here>

1. **Query Language**:
   - KSQL is a streaming SQL engine that enables real-time data processing and analysis, while riko is a Python library focused on ETL (Extract, Transform, Load) tasks.

2. **Integration**:
   - KSQL is tightly integrated with Apache Kafka for stream processing, whereas riko can be integrated with various data sources and storage solutions beyond Kafka.

3. **Development Ecosystem**:
   - KSQL provides a standalone server and interface for writing SQL queries, while riko is a Python library that requires coding and scripting for workflow development.

4. **Real-time Processing**:
   - KSQL is optimized for real-time stream processing and continuous queries on Kafka topics, whereas riko focuses on batch processing and data transformation tasks.

5. **Community Support**:
   - KSQL benefits from the larger Apache Kafka community for support and development, while riko relies on the Python community for enhancements and updates.

6. **Complex Event Processing**:
   - KSQL is proficient in handling complex event processing scenarios and real-time analytics, whereas riko specializes in data transformation and simplifying ETL workflows.

In Summary, KSQL and riko differ in their query languages, integration capabilities, development ecosystems, real-time processing optimizations, community support, and focus on event processing versus data transformation tasks.