Apache Kafka supports incredibly high throughput by partitioning topics and allowing producers to send multiple messages to different partitions simultaneously. Compression can also improve throughput and efficiency by reducing network traffic, but it's essential to consider the compression type and batch size to achieve optimal performance. The producer's compression type should be set to match the topic-level compression type whenever possible, as brokers will recompress data if they don't. Compressed data must be decompressed by consumers, which can impact CPU, network, and disk utilization. It's crucial to coordinate compression types across producers to achieve optimal end-to-end performance. Additionally, encrypted data should not be compressed, and default configuration settings should be double-checked for consistency between client and original distribution.