Financial services · Snowflake
Mercury Turns Fresh Data into Faster Product Decisions with Snowflake Openflow
Public case study · not a Metric Oak engagement
- Minutes of data latency to Snowflake, down from 30-60+ minutes
- 1-3
- Replication incidents since the migration
- 0
- Days to resync database, down from a week previously
- ~2
What happened
The story in brief
A US fintech providing banking for startups needed fresher data to make product decisions. Using Snowflake Openflow for ingestion, it cut data latency into Snowflake from up to an hour to a few minutes and freed engineering time.
See the full financial services benchmarkPlanning something similar?
Cloud data migration
Legacy warehouse to lakehouse, with parallel-run validation. Senior engineers, fixed scope, measured results.
Frequently asked questions
What results did Mercury report?
Mercury reported 1-3 minutes of data latency to Snowflake, down from 30-60+ minutes; 0 replication incidents since the migration; ~2 days to resync database, down from a week previously, according to its customer story published by Snowflake.
Which platform and technologies did Mercury use?
Mercury used Snowflake, including Openflow.
How do these results compare with other financial services programs?
See our financial services benchmark for median cost reductions and speed-ups across published results in the industry.
Source
Customer story published by Snowflake: Mercury Turns Fresh Data into Faster Product Decisions with Snowflake Openflow (opens snowflake.com in a new tab) on snowflake.com. Figures as published, retrieved 27 October 2026. The summary above is Metric Oak's own. This is not a Metric Oak engagement.
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