5 Hidden Costs of Running Real-Time Workloads on Snowflake (and How to Calculate Them)

Organizations initially chose Snowflake for its batch analytics capabilities, providing timely reports and data refreshes without the need for real-time responses. However, as demands for real-time data processing grew, costs surged due to the 24/7 operation of large warehouses, developer time spent on optimizations, and the complexity of integrating multiple tools to meet service level agreements. To address these issues, SingleStore offers a solution that offloads high-frequency, low-latency queries, reducing Snowflake credit consumption and tool sprawl, while improving developer productivity and enabling faster feature delivery. A real-world example of a global bank using Snowflake illustrates significant cost savings and efficiency improvements by integrating SingleStore, resulting in a 72% reduction in total operational costs. This approach allows businesses to maintain their existing Snowflake investments for batch analytics while enhancing their architecture to meet real-time, AI-driven demands.

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