Databento.
Usage-based institutional market data with normalized schemas and full order-book depth.
Overview
Databento's proposition is institutional data without institutional procurement: pay-per-use pricing, a single normalized schema across venues and asset classes, and access to raw, full-depth (MBO) history that traditionally required direct exchange relationships. For microstructure research and execution modeling, that depth is the product.
Where it fits
- Quant teams doing microstructure, execution-cost, or order-book research.
- Funds that want exchange-grade data quality with transparent, usage-based cost.
- Backtests that must model queue position and book dynamics honestly.
Constraints to weigh
- Usage pricing requires cost discipline in exploratory research loops.
- Depth data volumes demand real storage and processing infrastructure.
- Coverage, while expanding, should be verified per venue and history range.
In an agentic workflow
Normalized schemas matter disproportionately for autonomous pipelines: an agent consuming one consistent format across venues has a smaller surface for silent parsing errors — the class of failure that data-integrity guardrails exist to catch.
This profile is an independent editorial description; verify current pricing, licensing, and capabilities directly with the provider. Not affiliated with or endorsed by Databento.