DatabentoHow to build an order book (DoM) visualization using Databento, React, and RustBuild a web-based application to visualize market depth from L2 market data. Recommended tools and frameworks, code sample, and live demo.Sep 24Sep 24
DatabentoMatching Engines in 3 Minutes: Terminology Guide for Traders and DevelopersFor algorithmic traders, researchers, developers. Learn about colocation, proximity hosting, wire protocols, DMA, matching algorithms.Sep 12Sep 12
DatabentoBehind the scenes: How we built the world’s fastest cloud-based ticker plant at DatabentoA fast real-time market data feed — built with Rust, FPGAs, colocation, kernel bypass, layer 1 switching, zero-copy messaging, and more.Sep 91Sep 91
DatabentoGetting futures tick sizes and notional tick values in Python with DatabentoLearn how to get futures tick sizes and notional tick values at scale with Python and Databento — almost 800,000 instruments in 10 seconds.Sep 9Sep 9
DatabentoHow to calculate VWAP in Python with Databento and pandasThis guide explains the VWAP, its formulation and use cases, and how you can compute it quickly in Python with data from Databento.Aug 29Aug 29
DatabentoWriting a stock screener in Python with DatabentoScan over 600,000 instruments and compute ranking metrics like volume, average spread, depth, and largest pre-market movers in seconds.Aug 27Aug 27
DatabentoAn introduction to matching engines: A guide by DatabentoMatching engine architecture, gateways, latency, matching algorithms, port optimization, feed arbitration — how they affect your trading.Aug 26Aug 26
DatabentoLow-latency tuning guide for Linux and trading systems“How to tune a server/Linux for low latency” is a question that gets asked a lot. In most cases,Aug 22Aug 22
DatabentoLies, damned lies, and latency — Behind Databento’s NTP time serviceShortly after Databento launched its real-time market data, we had a big problem: Some customers were reporting negative latencies when…Jul 2Jul 2
DatabentoTop 6 things about daily market data that even institutional traders get wrongCommon mistakes when working with market data. And why nanoseconds matter even when you’re using daily settlement prices.Jun 141Jun 141
