SpiderRock was recently featured in a DataDrivenInvestor article, The Complete Guide to Building a Live Options Database in Python, which explores how to turn real-time options analytics into a structured, queryable dataset. 

The piece walks through a practical Python-based workflow for capturing live data and storing it in a lightweight database. Instead of relying on one-time snapshots, the approach focuses on continuously collecting analytics so they can be queried, compared, and revisited over time. 

This shift from transient data to persistent infrastructure is what makes the difference. With stored analytics, it becomes possible to analyze how volatility surfaces evolve, monitor changes in skew, and reconstruct past market conditions with much greater clarity. 

The tutorial keeps the build intentionally simple, showing how accessible this type of pipeline can be when working with clean, normalized data. Rather than spending time on heavy infrastructure, the focus stays on creating a usable dataset that supports real analysis. 

You can read the full article here: The Complete Guide to Building a Live Options Database in Python | by Nikhil Adithyan | May, 2026 | DataDrivenInvestor

About SpiderRock Data and Analytics 

SpiderRock Data & Analytics is a division of  SpiderRock Technology Solutions, a provider of industry-leading options trading solutions. SpiderRock Data and Analytics is an exchange-licensed redistributor of market data, providing US stocks and options market data in a raw and normalized format.   

SpiderRock’s proprietary live analytics offer low-cost delivery of market data and options analytics without requiring clients to make a significant investment in infrastructure. In addition, SpiderRock’s robust historical datasets updated daily from live markets are ideal for research, back testing, and making data-driven decisions. 

For more information, visit https://www.spiderrock.net/data/, follow us on X at @SpiderRockChi, and visit our LinkedIn page.

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