To build scalable, high-throughput event streaming systems—especially using Snowplow and platforms like Kafka or Kinesis—follow these best practices:

• Use distributed architecture: Leverage scalable stream platforms (Kafka, Kinesis) to handle growing data volumes.
• Partition data effectively: Partitioning ensures parallelism and helps maximize throughput.
• Apply compression: Use formats like Avro with compression (e.g., Snappy) to reduce message size and improve transmission efficiency.
• Ensure fault tolerance: Use message replication, acknowledgments, and retries to ensure reliability.
• Monitor performance: Continuously track system metrics and resource usage to identify bottlenecks and optimize throughput.
  
  

Snowplow’s enriched event data integrates naturally with such architectures, ensuring performance under heavy loads.