Tiger Data × Easee
Tiger Data x Easee: One database instead of two for 1M+ EV chargers
Storage footprint reduced from 15.6 TB to 8–10 TB (35–50% reduction)
Dual-stack operational burden to single-platform simplicity
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Why it works
The story is grounded in a concrete before/after architecture comparison with specific storage numbers, making the efficiency claim credible rather than vague. The compression-tuning anecdote (compress-after window iterated from 30 days to 22 days to 1 day) gives readers a replicable mechanism, not just a headline outcome. The secondary Clarity angle is real but subordinate: consolidated visibility is framed as a benefit of consolidation, not the primary win.
Steal this
Show the parameter-tuning iteration in detail. Walking through 'we tested 30 days, then 22 days, then 1 day, and here is what each step revealed' turns a generic compression claim into a believable, repeatable lesson that engineers trust.
Click to enlarge ↗ This is editorial commentary and curation. The case study, screenshot, and all metrics are Tiger Data's published work; we link to the source and lead with our analysis.