How Glooko Turns 3B+ Data Points/Month into Lifesaving Diabetes Healthcare with Tiger Data

Glooko, a diabetes monitoring solution used by over a million patients, successfully migrated its substantial medical data workload from a document database to Tiger Cloud, achieving significant cost and performance improvements. Faced with challenges such as sluggish ingestion, data bloat, slow queries, and no retention policies, Glooko sought a more efficient architecture to manage over 100 million new data points daily. The transition to Tiger Cloud's managed Postgres platform, optimized for time-series data, resolved these bottlenecks by decoupling compute and storage, implementing policy-based compression, and aligning query patterns with clinical needs. This shift not only reduced storage and compute costs, with compression ratios reaching up to 97%, but also accelerated query speeds from four minutes to half a second. The new architecture provided a more stable ingestion process and positioned Glooko to handle future data growth more effectively, with plans to consolidate all medical data collections into Tiger Cloud for enhanced performance and scalability.

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