Use cases
Polygon RPC for scrapers and data collection jobs
Scrapers fail when shared RPCs start rate-limiting, timing out, returning stale reads, or behaving differently under repeated calls. BlazingNode gives Polygon data jobs clear request volume, included traces, and simple add-ons when collection grows.
Last updated: July 8, 2026.
Use-case navigation
Who this is for
Scrapers need monthly volume more than burst
- Many scrapers run continuously.
- A high RPS ceiling is less useful if the monthly quota is too small.
- Monthly volume tells you how much data collection you can actually run.
- Burst is useful for short catch-up periods, not the main operating model.
| Symptom | Likely cause | Recommended fix |
|---|---|---|
| 429s after a few minutes | Concurrency too high or endpoint quota pressure | Throttle and budget request concurrency |
| Random timeouts | Tail latency or heavy methods | Reduce parallelism and chunk the workload |
| Stale block reads | Endpoint lag | Monitor latest block freshness |
| Duplicate processing | Retries without idempotency | Checkpoint and dedupe |
| Monthly quota gone early | Request planning failure | Add volume packs or upgrade |
| App logic blamed incorrectly | RPC variance | Compare the same job on a cleaner endpoint |
Responsible scraper architecture
Respect provider limits and platform terms. This page is about collecting public chain data responsibly, not bypassing limits.
What to test in the 72-hour mainnet trial
- Replay one scraper job
- Run the same worker count
- Compare p95 and p99
- Record 429s and timeouts
- Check stale latest block
- Measure requests per successful record
- Estimate monthly volume
BlazingNode plan fit for scrapers
| Scraper workload | Suggested plan | Why |
|---|---|---|
| Light monitor | Builder | 20M monthly requests at 300 RPS for smaller repeated collection |
| Daily production scraper | Operator | 45M monthly requests at 300 RPS for steadier jobs |
| Many workers / sustained collection | Pro | 90M monthly requests at 300 RPS for larger recurring demand |
| Heavy ETL / multiple data jobs | Business | 160M monthly requests at 500 RPS for large pipelines |
| Temporary catch-up | Extra 20M request packs | Monthly volume gap is temporary (39 USDC per pack) |
| Short campaign or event spike | +100 RPS 72h Burst Pass | Lift peak throughput from 300 RPS to 400 RPS for 3 consecutive days (72 hours) |
| Failed transaction or data debugging | Included traces / trace bundle | Trace volume can become its own constraint |
When to add extra 20M request packs
- Use extra volume when the scraper needs more monthly headroom but the 300 RPS baseline is plenty.
- If you keep buying multiple packs every month, upgrade.
- Operator 45M + one 20M pack = 65M for 138 USDC.
- Operator + three packs = 105M for 216 USDC, so Pro (90M) at 199 USDC is the cleaner recurring fit.
Continuous scraper? Buy volume, not burst.
BlazingNode vs shared cloud RPC for scrapers
Standard shared endpoints can work for basic prototypes or light jobs. For continuous repeated data collection, shared cloud endpoints often fail under bursty load in ways that look random. Dedicated RPC should be justified by fewer retries, fewer failures, clearer limits, and less debugging time.
FAQ
Can I use BlazingNode for scraping Polygon data?
Yes, for responsible collection of public blockchain data through RPC. Keep usage within plan limits and applicable platform terms.
How many requests does a scraper need?
It depends on worker count, polling frequency, checkpointing, retries, and how much data you collect per record. Continuous jobs often consume more monthly volume than expected.
Should I use extra volume or a higher plan?
Use extra volume for temporary catch-up or uneven months. Upgrade when you keep buying multiple packs every month.
How do I avoid 429s?
Throttle worker concurrency, add backoff, classify errors cleanly, and budget monthly volume instead of relying on repeated retries.
Can I run multiple workers?
Yes, but worker count should stay aligned with your plan limits and request budget. More workers without rate control usually creates retries and waste.
Is scraping blockchain data allowed?
Collecting public chain data is different from abusing provider infrastructure. Respect provider limits, platform terms, and your plan boundaries.