Case studies / Data foundations

Data foundations · Grocery retail

Teradata to Snowflake, at grocery-retail scale

One of the largest grocery retailers in the US was running on an aging 180TB Teradata Enterprise warehouse. We partnered with their own engineering teams to migrate the whole warehouse to Snowflake on Azure — without disrupting a business of 1,500+ stores and 30 million-plus customers.

30%
Lower cost

Versus Teradata, via Snowflake's pay-as-you-go model and elastic scaling.

40%
Faster queries

On critical batch workloads, using dedicated warehouses.

180TB
Migrated

The full warehouse of customer and product data, re-platformed end to end.

Sector
Grocery retail
Engagement
Multi-year warehouse migration program
Problem area
Data foundations
Confidentiality
Details anonymised

The challenge

An aging warehouse under a very large business

The client's Teradata Enterprise data warehouse had become a constraint: 180TB of customer and product data, growing roughly 10TB a year, on a platform that was expensive to run and hard to scale — for a business where reporting SLAs are not optional.

Before

  • 180TB Teradata Enterprise warehouse, growing ~10TB/year
  • High running cost, limited elastic scaling
  • Performance pressure against reporting SLAs
  • Large body of legacy code tied to the old platform

After

  • Full warehouse migrated to Snowflake on Azure
  • 30% lower cost via pay-as-you-go and elastic scaling
  • Up to 40% faster queries on critical batch workloads
  • Re-designed schemas, validated data, ready to scale

How we approached it

Analyse, migrate at scale, then tune for cost and speed

01

Redesign for Snowflake

We redesigned the database schemas for Snowflake instead of lifting the legacy Teradata structures across unchanged.

02

Automate conversion at scale

We developed the ETL with automated script generation to expedite legacy-code conversion across the warehouse.

03

Tune for cost and critical-workload speed

We tuned elasticity and dedicated warehouses over 10,000+ engineering hours and 24 months, delivered alongside the client's teams.

Under the hood

SnowflakeMicrosoft AzureAzure Data Lake StoragePythonSQLStored proceduresApache Kafka

Next step

Carrying a legacy warehouse you've outgrown?

We re-platform large, business-critical data warehouses onto modern cloud foundations — cutting cost and lifting performance, without disrupting the business that runs on them.

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