Warehouses sized for the work.
Snowflake, BigQuery, Redshift, ClickHouse and the open lakehouse stack. Sized, modelled and priced for the scale you're at — and the scale you're going to.
The problem we solve
Most warehouse decisions are made early, casually, and become very expensive to revisit. Wrong warehouse, wrong modelling, wrong access patterns — and the bill grows with the data. We design warehouses around your actual query patterns, with the cost discipline most teams only develop after their first six-figure surprise.
What we ship
- 01Warehouse selection: Snowflake, BigQuery, Redshift, ClickHouse, Postgres
- 02Lakehouse on object storage with Iceberg or Delta
- 03Dimensional modelling with star and snowflake schemas
- 04Partitioning, clustering and materialization strategies
- 05Access control and per-team data marts
- 06Cost monitoring with per-query attribution
- 07Migration between warehouses without downtime
- 08Query optimization on existing warehouses
- 09Federated query across warehouses where it fits
What you receive
- Production warehouse with documented modelling and access patterns
- Cost monitoring with per-team attribution
- Migration runbook for moving between warehouses
- Optimization report — frequently with material cost savings
Stack we reach for
Ideal for
- → Companies whose warehouse bill is becoming material
- → Teams outgrowing Postgres analytics queries
- → Data teams considering Snowflake → BigQuery migration (or vice versa)
- → Organizations adopting an open lakehouse alongside cloud warehouses
How an engagement runs
- 01
Query audit
Understand the real workload — query patterns, latency requirements, growth trajectory.
- 02
Design
Warehouse choice, modelling, partitioning, access patterns — written down with trade-offs.
- 03
Implementation or migration
Build new or migrate existing. Cutover with parallel running until confidence is built.
- 04
Optimize & monitor
Cost dashboards, query optimization passes, on-call handoff.
How to engage
Warehouse Audit
Cost and performance audit with prioritized recommendations.
Warehouse Build
Greenfield warehouse with modelling, access and cost discipline.
Warehouse Migration
Move from one warehouse to another with parallel running and documented cutover.
Frequently asked.
01Snowflake or BigQuery?
Both excellent. BigQuery for Google-native stacks and ad-hoc analytics. Snowflake for everything else, especially multi-cloud. ClickHouse where latency dominates cost. We'll model the costs on your real workload before recommending.
02Do we need a lakehouse?
If you have meaningful storage costs, mixed structured / unstructured data, or want vendor independence — yes. For most companies, a managed warehouse is the right answer for years.
Have a problem worth solving well?
Tell us the outcome you want. We'll tell you what it takes — honestly, within a week, in writing.
Start a conversation