Apache Kafka is critical for real-time streaming, but its costs, especially with Confluent, can be prohibitive.
AutoMQ offers a fresh take: a cloud-native Kafka implementation that reduces costs by rethinking traditional architectures.
Preconditions for Comparison
Peak Throughput: 0.1 GB/s
Average Throughput: 0.01 GB/s
Monthly Data Transfer: 25,920 GB
Storage Volume: 2,592 GB
Architecture: Multi-AZ (AWS)
Data Retention: 3 Days
Key Cost Differences:
Confluent Total: $17,369/month
AutoMQ Total: $718/month (95.8% less) How?
Stateless Brokers: No shared-nothing overhead.
Shared Storage: Amazon S3 eliminates cross-AZ replication costs.
Elastic Scaling: Decouples compute and storage for efficiency.
Core Benefits: Massive cost savings: Compute (-94.7%), Network (-99%), Storage (-78.3%).
Simpler operations with cloud-native scaling.
Retains Kafka's core performance without heavy infrastructure.
For anyone working with Kafka: Is this a sustainable solution for cost reduction?
Would you consider migrating to a cloud-native Kafka setup like AutoMQ?
As someone who works with Confluent Kafka I'm not happy with there pricing structure. While the cost savings look good I'd need a much larger Confluent bill to consider moving off Confluent. The cost savings appears to be about the cost of a developer. With complex systems using many micro services to communicate with Kafka the switching cost is not worth it at a small scale given the business values developers could provide instead of doing the switch. When your talking about much larger data volumes or multiple clusters across multiple regions then the math starts to look better.
I agree with you. If we have more data, it can definitely be more cost-effective.
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