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Best practices: scalable architectures for data systems
Scalable data architectures in 2025 demand more than adding servers—they require modularity, elasticity, and deep observability. This guide breaks down modern best practices, from event-driven designs and data mesh to storage-compute decoupling and AI-native architectures, with real-world case studies from Netflix, Uber, and Spotify.
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Empirical: throughput comparison of streaming architectures
This empirical analysis benchmarks the throughput of modern streaming architectures, comparing Apache Kafka, Apache Pulsar, Redpanda, and Flink-based pipelines. Using standardized workloads and realistic latency constraints, we dissect their design trade-offs, operational costs, and observed performance under varied load conditions.