Tree of Thought for Data Pipeline Design

Use tree-of-thought reasoning to design this data pipeline.

## Data Requirements
{{data_requirements}}

## Sources and Sinks
{{sources_sinks}}

## Processing Requirements
{{processing_requirements}}

Explore design options:

**Branch 1: Batch Processing**
├── Apache Spark approach
│   ├── Pros: Scalability, ecosystem
│   ├── Cons: Latency, complexity
│   └── Suitability assessment

**Branch 2: Stream Processing**
├── Kafka Streams/Flink approach
│   ├── Pros: Low latency, exactly-once
│   ├── Cons: Operational complexity
│   └── Suitability assessment

**Branch 3: Lambda Architecture**
├── Batch + Stream hybrid
│   ├── Pros: Best of both
│   ├── Cons: Dual maintenance
│   └── Suitability assessment

**Branch 4: Simplified Modern Stack**
├── Snowflake/BigQuery approach
│   ├── Pros: Simplicity, managed
│   ├── Cons: Cost, vendor lock-in
│   └── Suitability assessment

**Recommendation**
Selected approach with implementation outline.