Choosing the right data source is critical for quantitative development, but the requirements differ significantly between backtesting and real-time trading. This article provides a practical checklist to evaluate data sources like Tushare, AkShare, TickDB, and real-time APIs. For backtesting, completeness of delisted stocks and consistent adjustment methods are paramount. For real-time dashboards, stable push mechanisms and clear timestamp semantics are essential. The article avoids ranking services and instead offers a framework to assess data quality, coverage, and integration complexity. It also highlights common pitfalls, such as assuming 'covers A-share' means the same thing for different use cases. For developers building quantitative systems, this guide helps avoid costly mistakes in data source selection.
A practical guide to selecting financial data APIs for quant development, comparing Tushare, AkShare, TickDB, and real-time APIs.