datatypes

Independent data engineering practice

Systems for data
that matters.

Datatypes designs, repairs and operates high-performance data systems for organisations where correctness, latency and evidence are non-negotiable.

Scope
Architecture → operation
Scale
Startup → enterprise
Bias
Measured → durable
01

Practice

Engineering across the full life of a data system.

01.1

Platform architecture

Clear boundaries, explicit ownership and infrastructure chosen for the workload rather than the diagram.

01.2

Pipelines and streaming

Batch and event systems with observable state, repeatable recovery and predictable operating costs.

01.3

Performance engineering

Profiling, query and storage design, throughput analysis, compression and the removal of accidental work.

01.4

Technical assurance

Independent review, platform rescue and direct technical leadership when a system has become difficult to trust.

02

Fields

Specialist work, fitted to the institution.

Work spans new platforms for small teams and exacting delivery inside governments, telecommunications companies and global consultancies. The environment changes. The engineering standard does not.

  • 01Digital assets and crypto
  • 02Government
  • 03Blockchain protocols
  • 04Artificial intelligence
  • 05Telecommunications
  • 06Consultancies

Clients range from early-stage startups to Big Four consultancies.

03

Research

Delta Sigma

Below the abstraction.

Datatypes is informed by Delta Sigma, an independent mathematics research company investigating extremely low-level solutions to fundamental computational problems.

The research includes new approaches to compression, sorting and the mathematical structure beneath high-performance systems.

Visit Delta Sigma
04

Method

A small set of working rules.

  1. 01

    State the invariant.

  2. 02

    Measure before tuning.

  3. 03

    Make recovery ordinary.

  4. 04

    Document the reason.