Recently, a senior software engineer at Coinbase analyzed one of the largest publicly available Polymarket datasets to date: over 400 million trades going back to 2020, totaling 36GB of compressed data. When asked how he managed to pull that volume of historical data from Polygon without getting blocked by rate limits, his answer was simple: he used Ankr as the RPC provider.

Happy to help 🤝 https://t.co/xlJHpF4XZv

— Ankr (@ankr) February 13, 2026

Since Ankr’s Premium Pay-As-You-Go Plan supports approximately 1,222 more Requests Per Second on average than our top five competitors’ premium plans, Ankr is the natural choice for those seeking to conduct major market research.

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Rate Limits & Throughput: The Hidden Bottleneck in Onchain Research

Blockchains are public, but access to them is mediated through RPC endpoints. Every log, transaction receipt, block header, and contract call is retrieved through RPC requests, and those requests are rate-limited (maximum requests per second, aka throughput or RPS, allowed before requests get rejected).

When you are working at small scale, these rate limits don’t matter as much, but when you are working at research scale, they define what’s possible. Pulling years of historical data requires:

• Scanning millions of blocks
• Querying logs across many contract addresses
• Handling pagination limits
• Retrying failed requests
• Validating completeness
• Re-running portions after code adjustments
• Cross-checking decoded events against raw receipts

When rate limits are restrictive, the entire process slows to a crawl or even reduces data quality.

Rate Limits Determine Feasibility

A strict rate limit doesn’t only increase the time it takes to collect data, it changes what you can realistically attempt when building models. Imagine trying to backfill 400 million trades across multiple years. If you are capped at low requests per second, you face several tough tradeoffs. You could have to choose between:

• Reducing granularity
• Widening block ranges and risk missing logs
• Skip validation passes
• Avoid retries to save time
• Abandon full history and settle for sampling

Each compromise of course degrades the dataset. But higher rate limits eliminate those compromises and ensure researchers can pull complete histories, validate multiple times, and build production-grade datasets rather than partial snapshots.

How Ankr Changes the Equation

Ankr’s Premium plan supports 1,500 RPS, much more than comparable paid plans by other providers. This fundamentally shifts the economics of research scale ingestion.

Higher sustained RPS means researchers can:

• Download complete blockchain history much faster
• Higher confidence multi pass validation (double and triple check data for accuracy)
• Parallel decoding at scale (process huge amounts of data at the same time)
• Less dependence on third party indexers
• Greater control over raw data integrity

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The Bigger Picture: Turning Public Chains Into Usable Data

Blockchains are often described as transparent and public. Technically, that is true. Practically, it depends on access.

Without sufficient throughput, public becomes synonymous with slow, slow is impractical, and impractical will always mean unused.

High rate limits turn public blockchains into accessible research environments:

• Large-scale historical analysis
• Real-time monitoring
• Production analytics pipelines
• Institutional-grade data products
• Open datasets that benefit the entire ecosystem

The difference between theory and practice is infrastructure.

Powering Institutional-Grade Onchain Research

The Polymarket dataset example is not an isolated case. High-throughput RPC infrastructure is not only critical for independent researchers. It is foundational for the largest onchain analytics platforms in the industry.

Ankr powers data-heavy research platforms like Nansen and Sentora (formerly IntoTheBlock), whose products depend on continuous, high-speed/throughput, multi-chain blockchain access.

These platforms serve analysts, traders, funds, and institutions making real financial decisions. For them, infrastructure is core to their product reliability and competitive advantage.

More on our work with Nansen →

Our Sentora case study →

Final Thoughts

As onchain markets mature, the edge will not belong to those who simply have ideas, but to those who can access, verify, and iterate on data at scale. The next generation of analytics, AI-driven trading systems, and institutional research platforms will be built on raw, high-velocity chain access.

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