Trading Time-Series Databases
Storage designed for the query patterns research actually uses.
Every model rests on its data. Gaps, revisions, timezone errors and survivorship problems produce backtests that look excellent and trade badly. We build pipelines where data problems surface loudly instead of silently.
On a trading time-series databases engagement this means starting from what you already have — an idea, a spreadsheet, a running system, or a set of results that do not add up — and working from there rather than insisting on a rebuild. Where the honest answer is that the work is not worth doing, that is what you will be told.
What you get
- Ingestion from vendor, broker and exchange sources into one store
- Time-series storage designed for the query patterns research actually uses
- Automated quality checks: gaps, outliers, stale feeds, revision tracking
- Point-in-time correctness so backtests cannot see the future
How the work runs
Scope
A short call and a written scope: what the system must do, what data it needs, what counts as done. Fixed price where the scope allows it.
Build
Work in reviewable increments, with running code you can see rather than a status update. Assumptions are surfaced as they arise, not at the end.
Test
Independent testing against the acceptance criteria agreed in the scope, including the failure cases.
Handover
Source code, documentation and a walkthrough. You own the result and can maintain it without us.
Tell us what you are trying to build
Describe the problem and we will tell you plainly whether we can help, roughly what it would take, and what it would cost. If it is not a fit, we will say so.
Build My Trading Data Pipeline