A cloud operations room at night, engineers watching wall displays of infrastructure health

Platform

AWS

Redshift, Glue, S3 and the services around them, put together into something a small team can genuinely run day to day.

Book a discovery call

The limit on most AWS data platforms is not the technology. It is who is on call at 3am.

An AWS console view showing EC2 service health, instance counts, spend for the month and instances by region

What we do with AWS

Redshift

Sized against how many people query at once, with priorities set so an analyst exploring cannot slow down the overnight reporting run.

Glue and Lake Formation

Cataloguing and permissions that still make sense when someone asks who could read a particular dataset, and when.

Storage structure

How files are organised and how long they are kept, decided deliberately rather than accumulated over years.

Everything defined as code

So the whole platform can be rebuilt from scratch, and every change is reviewed before it happens.

Cost controls from day one

Tagging and budget alerts set up before the platform grows, rather than after the first surprising invoice.

Works with

Migration with minimal downtime

Moving legacy systems across in stages, so the business keeps running while it happens.

Glue, Lambda, Kinesis and Redshift

The pipeline building blocks, chosen for the job rather than used because they are there.

SageMaker, QuickSight and Athena

Machine learning, dashboards and querying files directly where a warehouse would be overkill.

What clients use it for

Serverless applications

Lambda, API Gateway and DynamoDB, where you want the thing to cost nothing when nobody is using it.

Security and audit

IAM, GuardDuty and CloudTrail, set up so you can answer who did what and when.

Cost management

Cost Explorer and Trusted Advisor, with tagging in place so the numbers mean something.

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

An AWS data mesh architecture diagram, showing producer and consumer domains either side of a federated governance layer

Three colleagues reviewing work on a monitor together

The people who pitch do the work

Small senior teams. There is no arrangement here where an experienced partner wins the engagement and somebody else delivers it.

The rest of the stack we work in

Common questions

Redshift or Snowflake on AWS?

Redshift fits more tightly with the rest of AWS and can be cheaper at steady usage. Snowflake is usually easier to run with a small team. Honestly, headcount decides this more often than performance does.

Serverless or provisioned?

Serverless suits unpredictable, spiky usage. Provisioned suits steady heavy usage. Many organisations want both, split by workload.

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.