A LinkedIn post from ScyllaDB highlights a case study involving online travel platform Agoda, which reportedly experienced a 50-fold increase in server traffic between January 2023 and February 2025. The post indicates that this growth created engineering challenges related to bursty traffic, volatile cache hit rates, and cold-cache scenarios while targeting 10 ms P99 latencies.
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According to the post, ScyllaDB is promoting a technical session by Agoda lead software engineer Worakarn Isaratham that explains how Agoda scaled its feature store under these conditions. For investors, this type of reference account may suggest that ScyllaDB’s database technology is being applied in demanding, latency-sensitive production environments, potentially strengthening its positioning for high-scale enterprise and travel-technology workloads.
The emphasis on maintaining strict latency targets during a large traffic spike could be interpreted as underscoring performance and scalability as key differentiation points for ScyllaDB. If similar high-growth customers adopt or expand use of its technology, this could support longer-term revenue growth and deepen its presence in data infrastructure markets that prioritize real-time personalization and feature-store architectures.