Git packfiles use delta compression, storing only the diff when a 10MB file changes by one line, while the objects table stores each version in full. A file modified 100 times takes about 1GB in Postgres versus maybe 50MB in a packfile. Postgres does TOAST and compress large values, but that’s compressing individual objects in isolation, not delta-compressing across versions the way packfiles do, so the storage overhead is real. A delta-compression layer that periodically repacks objects within Postgres, or offloads large blobs to S3 the way LFS does, is a natural next step. For most repositories it still won’t matter since the median repo is small and disk is cheap, and GitHub’s Spokes system made a similar trade-off years ago, storing three full uncompressed copies of every repository across data centres because redundancy and operational simplicity beat storage efficiency even at hundreds of exabytes.
Under load, this creates GC pressure that can devastate throughput. The JavaScript engine spends significant time collecting short-lived objects instead of doing useful work. Latency becomes unpredictable as GC pauses interrupt request handling. I've seen SSR workloads where garbage collection accounts for a substantial portion (up to and beyond 50%) of total CPU time per request. That's time that could be spent actually rendering content.
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现在，比任何时候我都更怀念史蒂夫那种独特而清澈的清晰感。超越想法与愿景本身，我怀念的是他那种能够为混乱建立秩序的洞见。
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更致命的是，算力成本的下降并未如预期般刺激需求爆发，反而引发了行业“通缩恐慌”。
But more than 2,000 job applications later he is still hunting, trying to make ends meet with jobs in package delivery and landscaping.。关于这个话题，safew官方版本下载提供了深入分析