vs OANDA

Looking for OANDA
historical data?

OANDA's historical data comes with workflow friction. Get audited, backtesting-ready Parquet data with release coverage and a one-time purchase.

Side-by-side comparison

FeatureOANDAHistorical FX
Data historyLimited (varies by pair)Audited release coverage
Currency pairs~70 pairs74 coverage-reported folders
Pricing modelAccount requiredOne-time purchase
Download formatAPI onlyParquet now; CSV/MT4 rebuild pending
TimeframesMultiple7 (M1 to Weekly)
Data cleaningRaw dataSchema, OHLC, duplicate, and coverage audits
Backtesting readyRequires processingImmediate use

Why traders switch from OANDA

Deeper history

OANDA's API requires pagination and source-specific handling. Our files are packaged as local Parquet datasets with documented release coverage.

No API hassle

Skip rate limits and pagination. Download packaged datasets as files and load directly into pandas, R, or your backtesting platform.

One-time cost

No account maintenance or ongoing fees. Pay once, download your data, and use it forever for any project.

Pre-cleaned data

Release files are packaged for repeatable loading and validation. Load and backtest without rebuilding an API ingestion pipeline.

74
Coverage folders
300.4M
Audited rows
QA
Coverage report
7
Timeframes

Ready to upgrade your data?

Start with sample-first historical forex data, coverage reports, and a one-time purchase path after fulfillment checks are green.

Common questions

Is this data as accurate as OANDA?
It is a different product: audited historical OHLCV files for local research, with pair-specific coverage reports. Use OANDA when you need broker-native pricing or live account integration.
Can I use OANDA spreads with this data?
This is mid-price OHLCV data (bid+ask/2). For spread simulation, apply your broker's typical spread to the data. Most backtesting frameworks support this.
What if I need real-time data too?
Use our historical data for backtesting and OANDA's API for live trading. Many traders use this hybrid approach for best results.
Is the format compatible with my tools?
Parquet works with Python, R, DuckDB, Spark, and most modern data tools. CSV and MT4/MT5 conversion files are being rebuilt and are not sold until matching delivery artifacts are uploaded.