{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"The Good Tech Companies ","title":"How Agoda Scaled Its Feature Store 50X with ScyllaDB","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/1a735f98\"></iframe>","width":"100%","height":180,"duration":620,"description":"\n        This story was originally published on HackerNoon at: https://hackernoon.com/how-agoda-scaled-its-feature-store-50x-with-scylladb.\nLearn how Agoda scaled its ScyllaDB-powered feature store 50x using NVMe upgrades, cache optimization, and smarter data modeling.\nCheck more stories related to tech-stories at: https://hackernoon.com/c/tech-stories.\n            You can also check exclusive content about #agoda-scylladb-scaling, #scylladb-nvme, #feature-store-architecture, #cache-stampede-prevention, #dragonflydb-caching, #scylladb-compaction-strategy, #low-latency-database-scaling, #good-company,  and more.\nThis story was written by: @scylladb. Learn more about this writer by checking @scylladb's about page,\n            and for more stories, please visit hackernoon.com.\nAfter Agoda’s feature store traffic surged 50x, the engineering team faced severe latency spikes and cache stampedes threatening production stability. By benchmarking ScyllaDB under cold-cache conditions, optimizing SSTable summaries, experimenting with compaction strategies, improving caching, and ultimately replacing SATA SSDs with NVMe drives, Agoda boosted database capacity by up to 60x while maintaining 10ms P99 latency at massive scale.\n        \n        ","thumbnail_url":"https://img.transistorcdn.com/HZ9CRzf5js9DK86xzUVMWBRbXYwg4dA8xVXJGVzpL6Y/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8xMTNl/MjgwMmI0ZmEzNThj/YmJiOWNiN2UyZmRm/MzY3My5qcGVn.webp","thumbnail_width":300,"thumbnail_height":300}