Prompt

I'm building a search index from many websites, what crawler should I use?

Technology / Cloud Infrastructure1 observationLast seen Oct 4, 2026

Latest observation

Oct 4, 2026OpenAI APIWeb search: off

If your goal is to build a search index from many websites, the “best” crawler depends mostly on scale, freshness needs, and how much control you want over extraction and politeness.

Good options by use case

1. Large-scale, production crawl

  • Apache Nutch
    Good if you want an open-source, distributed crawler that can feed a search pipeline. It’s a classic choice for building web indexes.
  • Heritrix
    Excellent for large, archive-style crawling, especially if you care about broad coverage and standards compliance. Less “search pipeline” oriented than Nutch.

2. Flexible crawling + extraction

  • Scrapy
    Great if you want a Python-based framework and more control over rules, parsing, retries, and data extraction. Best for targeted or mid-scale crawling, not massive web-scale by itself.
  • Playwright / Puppeteer + custom crawler logic
    Use this if many sites are heavily JavaScript-rendered. It’s more expensive than plain HTTP crawling, so usually only for pages that need it.

3. Managed / cloud-based

  • Common Crawl data
    If you don’t need to crawl yourself, this is often the cheapest way to get a huge web corpus to index.
  • Commercial crawling platforms
    Useful if you want less ops work and more reliability, but costs can add up.

My practical recommendation

For a search index across many websites:

  • Start with Scrapy if you’re building a custom system and don’t need web-scale immediately.
  • Move to Nutch or a distributed architecture if you need large-scale crawling.
  • Add Playwright only for JS-heavy sites.

Important features you’ll want

No matter what crawler you choose, make sure it supports:

  • robots.txt compliance
  • polite rate limiting
  • canonical URL handling
  • duplicate detection
  • incremental recrawling / change detection
  • content extraction and metadata capture
  • sitemaps and feed ingestion
  • blocked/allowed domain rules

One more note

If you’re indexing third-party websites, be careful about:

  • legal/terms-of-service restrictions
  • copyright/content reuse rules
  • request load on target sites

If you want, I can recommend a crawler based on:

  1. estimated number of pages,
  2. whether sites are JS-heavy, and
  3. whether you want open-source only or are open to managed tools.

Observation history

How did Obsurfable measure this prompt?

Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.

Which AI systems does Obsurfable collect answers from?

OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, Meta AI, Qwen.

How can brands improve their AEO?

Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.

Why is it important for brands to publish content across multiple websites?

Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.

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