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Distributed Crawling

A curated collection of the best distributed web crawling systems for large-scale data collection across multiple nodes.

Quick answer

Distributed crawling choices depend on whether you are scaling a framework, running a batch web crawl, or preserving an archive. Scrapy and Scrapy-Redis fit Python crawler fleets, Nutch fits Hadoop-style batch crawling, Heritrix fits archival crawls with WARC output, and Frontera focuses on crawl-frontier orchestration.

Related guides

Best Open-Source Web Scrapers

Top picks in Distributed Crawling

  1. Scrapy

    Python crawler
    Fits Python teams that need async crawling, middleware, pipelines, and a framework that can be scaled with external queues.

  2. Scrapy Redis

    Scrapy workflows
    Fits existing Scrapy deployments that need Redis-backed queues, deduplication, and shared scheduling.

  3. Nutch

    Batch crawling
    Fits Java and Hadoop-style crawls that need plugin extensibility and search-engine indexing integrations.

  4. Heritrix

    Web archives
    Fits archival crawls that need WARC output, crawl controls, a web UI, and preservation-oriented operation.

  5. Frontera

    Crawl frontier
    Fits teams whose hard problem is URL priority, scheduling, deduplication, and distributed worker coordination.
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