Can I inspect before paying?
Typical vendor workflow
Often limited to docs, trials, sales pages, or small samples.
HistoricalFX workflow
Free EUR/USD sample, release coverage, sample audit report, and public methodology pages.
Forex Data Provider ComparisonCompare forex data providers by
Compare forex data providers by
workflow risk
TraderMade, Kibot, Tick Data, Massive, Dukascopy, and HistoricalFX solve different parts of the historical FX problem. The right question is not only who has data. It is how much ingestion, cleaning, validation, and maintenance work remains before a backtest can be trusted.
HistoricalFX Proof Layer
74
Verified symbols
518
Parquet files
300.4M
Full bundle rows
78.8M
Major rows
May 31, 2026
Latest packaged timestamp
What each provider really sells
Bigger vendors often win on breadth, source depth, or mature delivery tooling. HistoricalFX is deliberately narrower: proof-first local files, documented limitations, and audits that help buyers decide whether data is usable before repair work starts.
| Provider | Best fit | Buyer work remaining | Positioning signal |
|---|---|---|---|
| TraderMade | Teams that want API, spreadsheet add-ins, and bulk historical FX access from one vendor. | Integrate API or purchased files, then validate the exact fields, cadence, and backtest assumptions in your own workflow. | Markets historical FX access, bulk downloads, CSV delivery, and cleaned provider-aggregated data. |
| Kibot | Traders who want broad intraday market history, software compatibility, and updater tooling. | Choose packages, import into trading software, and still confirm assumptions around sessions, symbols, and strategy use. | Positions historical data as cross-checked, tested, verified, backtesting-ready, and updatable. |
| Tick Data | Institutions, researchers, and serious teams that need research-quality historical intraday market data and tooling. | Work with a more enterprise-style data solution and configure the delivery/tooling around the research stack. | Leads with clean research-ready data and the pain of collecting, formatting, maintaining, and updating intraday data. |
| Massive flat files | Developers who prefer S3-compatible bulk files and already know how to query compressed market-data datasets. | Set up flat-file access, download the right datasets, and build the validation and loading path. | Documents bulk compressed CSV delivery over an S3-compatible endpoint for historical market data. |
| Dukascopy/free-source workflow | Builders with time to script source pulls and maintain their own parsing, aggregation, and QA pipeline. | Download, parse, normalize, aggregate, dedupe, validate, classify gaps, and package files yourself. | Free access can be valuable, but raw access is not the same as a repeatable research dataset. |
| HistoricalFX | Traders and developers who want local files, proof assets, and a practical path from sample to backtest. | Inspect sample and coverage first, then buy a packaged release or start a scoped audit for existing files. | Focuses on coverage visibility, known limitations, sample-first validation, and starter audits before repair work. |
HistoricalFX Wedge
The gap we are filling
The blue ocean is not pretending data is scarce. It is becoming the proof layer between raw access and a trusted backtest: sample files, coverage reports, QA checks, audit deliverables, and source-backed repair recommendations.
See Clean Data WorkflowDo I still need data engineering?
Typical vendor workflow
Usually yes: API ingestion, file parsing, conversion, and validation remain your responsibility.
HistoricalFX workflow
Parquet-first local files, coverage reports, and customer audit tooling reduce the first-mile work.
Are gaps hidden?
Typical vendor workflow
Depends on vendor and source. Buyers still need to inspect the delivered file against expected sessions.
HistoricalFX workflow
Known-gap visibility is part of the product direction. We do not claim gap-free data or fabricate continuity.
What if I already have files?
Typical vendor workflow
Most vendors sell replacement data, not a decision report on your existing dataset.
HistoricalFX workflow
The $299 starter audit reviews customer files and recommends use, repair, quarantine, or exclusion.
Is there recurring update potential?
Typical vendor workflow
Large vendors already sell APIs, updates, or flat-file subscriptions.
HistoricalFX workflow
API/update waitlist is live; recurring refresh gets built only after real buyer demand is validated.
Start with proof, not a sales call
Use the assets below to decide whether HistoricalFX fits your workflow. If the sample or report does not match the problem you have, do not buy yet.
Free sample
Inspect schema, timestamps, columns, and loader fit before any paid order.
Release coverage
See what is packaged, how many files exist, and where known limitations remain.
Sample audit report
Review the kind of duplicate, OHLC, gap, and outlier checks used in the starter audit.
API/update waitlist
Tell us the pairs, cadence, and delivery format that would justify recurring refresh work.
Provider comparison questions
Is HistoricalFX better than TraderMade, Kibot, Tick Data, or Massive?+
Not universally. Those vendors may be better when you need broad APIs, enterprise sourcing, tick-level products, or established update tooling. HistoricalFX is focused on transparent backtesting workflow assets: sample files, coverage reports, known-gap visibility, and scoped audits.
Why not just use a free source?+
Use a free source if you have the time and skill to maintain the pipeline. The paid value is the work after raw access: normalization, duplicate checks, invalid OHLC checks, gap reporting, packaging, and repeatable loading.
Do you guarantee gap-free forex data?+
No. We do not sell fake continuity. Missing ranges must be source-observed to be repaired; otherwise they are reported as limitations.
What is the fastest path to decide if this fits?+
Download the free sample, inspect release coverage, and review the sample audit report. If you already have files, start with the starter audit or send scope first.
Choose the smallest useful next step
If you need packaged local files, start with the sample and major bundle. If you already have suspect files, start with scope or the starter audit.