Platform

Snowflake

A cloud data platform where storage and processing are charged separately, which removes the limit that was quietly rationing how much your teams could query.

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Flexible pricing does not lower your costs. It reveals how much demand you were suppressing.

What we do with Snowflake

Sizing it sensibly

Each workload gets the right amount of processing power, set to switch off when idle, based on how your teams actually query rather than defaults nobody has revisited since setup.

Knowing where the money goes

Spend traced back to team and workload, so conversations about the bill have evidence in them rather than opinions.

Access that stands up to an audit

Set up so you can answer who had access on a date in the past, not just who has access today. That second question is the one that gets asked.

Safe copies for development

Instant copies of production data that cost almost nothing, so people can test properly without touching live systems.

Near real-time updates

Where the business genuinely needs data within minutes rather than overnight, and only where that is genuinely needed.

Works with

Semi-structured data

JSON, Avro and Parquet handled natively, so you are not flattening everything before you can query it.

Runs on AWS, Azure or Google Cloud

Which matters if your organisation has already committed to one of them.

Connects to what you already use

ThoughtSpot, Tableau, Power BI and Looker for reporting. Fivetran, dbt, Informatica and Talend for moving and shaping data.

What clients use it for

Sharing data safely

Live, governed sharing with other teams, partners and customers, without sending anyone a file.

Data Marketplace

Third-party datasets available without a procurement exercise and an ingestion project.

Machine learning tools

DataRobot, H2O.ai, SageMaker, Azure ML and Vertex AI, plus SQL, Python and REST APIs for building your own.

Where it fits

We are not a reseller and we take no vendor commissions, so there is nothing riding on which platform you choose. What we care about is whether the setup can be operated by your team after we leave.

Recommended where it genuinely solves a problem you have, not as a default
Implemented as code in your repository, under your accounts
Handed over with runbooks for the failure modes we actually hit

A colleague drawing a systems diagram on a glass wall

We will tell you if this is the wrong tool

We take no commission from any platform on this site, so there is nothing riding on which one you end up choosing.

The rest of the stack we work in

Common questions

Our Snowflake bill keeps rising. Is that bad?

Not necessarily, but it should be explainable. Rising spend you can attribute to a team and a purpose is a business decision. Rising spend nobody can explain is the thing to fix.

Snowflake or Databricks?

If your work is mostly SQL reporting, Snowflake is usually the shorter path. If you have significant data science and streaming alongside it, Databricks earns its place. Plenty of organisations run both quite sensibly.

Ready to turn complexity into your next advantage?

Tell us what you are running today and what is not working. That is a more useful starting point than a platform comparison.