Compare Internet Archive Scraper Side by Side

Need to compare internet archive scraper across targets? Thirdwatch's Internet Archive Scraper turns it into structured rows — the fields you need, ready to export.

Skip the setup: Run this as a ready-to-go task on Apify — pre-loaded with the configuration from this guide.

Why Compare side by side works

Put the same fields side by side for every target — the deltas are where decisions happen. This guide shows the configuration that pulls internet archive scraper data from Internet Archive Scraper.

How does this compare to the alternatives?

Manual copy-paste works for a handful of rows; dedicated per-site scrapers on other platforms either gate the same data behind sign-in or charge flat monthly fees regardless of usage.

Why this Actor

• Purpose-built for Internet Archive Scraper — no generic crawling config to tune
• Pay-per-result pricing — you pay only for rows that come back
• Structured output ready for JSON/CSV export or API consumption
• No login, cookies, or API keys needed for the public surfaces it reads

How to do it in 3 steps

Step 1: Configure the input

Set the inputs as shown below — mode takes the targets, and the optional fields bound the run size.

Step 2: Run the Actor

Run it from the console, the API, or the linked saved task. One dataset row is written per record.

Step 3: Use the output

Every row carries the fields shown in the sample — export as JSON, CSV, or feed it straight into your pipeline.

{
  "mode": "search",
  "query": "apollo 11",
  "identifiers": [
    "nasa"
  ],
  "maxFilesPerItem": 50,
  "urls": [
    "apify.com"
  ],
  "waybackMatchType": "exact"
}

Each dataset row looks like:

{
  "record_type": "item",
  "identifier": "tp2rfbxnszkhqoposekc1zk25r7brwbtfmwif0oa",
  "title": "From 7 up to 70",
  "creator": "Lyft Mobile",
  "creators": [
    "Lyft Mobile"
  ],
  "description": "Chris Selin joins Adam and Polly to talk about what it was like as Lyft's team grew from 7 mobile developers up to 70. Topics include hackathons, managing long-running iOS feature development, xib vs. programmatic layout, and sustainability. Also, Chris's plans to time-travel possess Neil Armstrong for the week on the moon landing.",
  "mediatype": "audio",
  "collections": [
    "podcasts_mirror_bobarchives",
    "podcasts_mirror"
  ],
  "subjects": [
    "Podcast",
    "coding",
    "designing",
    "development",
    "mobile",
    "programming",
    "software",
    "transportationdevelopment",
    "feature",
    "layout",
    "ios",
    "xib"
  ],
  "languages": [],
  "date": "2019-10-31T00:00:00Z",
  "year": 2019
}

What to watch for

Rate the targets reasonably — large batches benefit from modest concurrency. Source sites may throttle heavy bursts; retry once and widen filters if a target surface is thin.

Related use cases

• Feed Internet Archive Scraper Data Into Your Pipeline
• Extract Internet Archive Scraper at Scale
• Monitor Internet Archive Scraper on a Schedule
• Export Internet Archive Scraper to CSV
• All Thirdwatch use-case guides

Run the Internet Archive Scraper on Apify Store — pay per result, free to try, no credit card to test.