Logiciel Solutions · Data Engineering
Staying on a legacy warehouse feels safe until the annual invoice arrives. Put in your volume and costs to see what migration to a modern lakehouse actually saves over three to five years.
Your numbers
Six inputs. Results update as you type.
Total managed data today including backups and replicas.
All-in annual cost per TB: compute, storage, licensing, and support.
Target platform cost per TB. Databricks, Snowflake on object storage, or similar.
Data volumes grow fast. 25–40% per year is typical for modern data teams.
Engineering effort, tooling, testing, and cutover for the migration project.
How many years to compare total cost of ownership.
The verdict
Adjust the inputs — results unlock when you submit.
We’ll send the detailed cost breakdown and have a data engineer walk through your specific platform, volume, and migration approach.
No spam. We’ll follow up only if it’s relevant.
How the math works. The warehouse cost compounds with your data growth each year: cost = TB × $/TB/yr × (1+growth)^year. The lakehouse uses the same curve at a lower per-TB rate, plus the one-time migration cost added once at the start. Total cost is summed across all horizon years. Savings = warehouse total − lakehouse total. Payback = migration cost ÷ (year-one warehouse cost − year-one lakehouse cost). Because data grows, the savings gap widens every year — the three-year number is typically conservative. This is a directional estimate to frame a decision, not a quote.
Logiciel Solutions · logiciel.io
