GoKawiilAnalysis argues Amazon S3's disk-era design is becoming outdated as SSD prices fall
A technical essay examines how Amazon S3 and similar cloud object stores, built around spinning-disk economics from two decades ago, now underpin most modern data architectures including data lakes, Kafka alternatives, and vector databases. The author notes S3's per-request throughput and latency limits stem from disk physics, forcing developers to add caching layers, batch writes, and separate metadata stores to work around them. The piece highlights that SSD prices have fallen steadily since S3's 2005 launch, narrowing the cost gap with hard disks to about 3x.
GoKawiil's interpretation of the reporting above, not reported fact.
The narrowing price gap between SSDs and disks suggests that storage systems designed around slow, high-latency disk assumptions may no longer be the optimal foundation for data infrastructure. This could imply that future cloud storage architectures might shift toward SSD-native designs that eliminate the workarounds—caching, batching, metadata stores—that current S3-based systems require. The essay frames this as a coming architectural inflection point, though it stops short of naming specific replacement technologies.
- S3's architecture reflects hard-disk economics from its 2005 launch, including high latency and low per-request throughput.
- Popular systems like Iceberg/Parquet data lakes, Warpstream, and Turbopuffer are all built atop S3 and inherit its limitations.
- SSD prices have dropped significantly, narrowing the cost gap with disks to roughly 3x, potentially undermining S3's core design rationale.
Source: btrblocks.com — Viktor Leis, 2026-09-25
Published there as: “S3 Is the Future, S3 Is the Past”
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