Glassdoor: scrapers and the official API, compared

Route map

Each line is one way to get Glassdoor data; each stop is a field you probably need. Green lines are catalogue Actors, ranked by the published formula.

Which route for which job

The catalogue Actors for Glassdoor return different records. "Only this route" lists the published fields no other Actor in this table returns, which is usually what decides the choice. Cost is the published per-result rate; start events and platform usage are extra.

Field matrix: who returns what

Every tool with a published output schema, against the 7 fields most Glassdoor jobs need. A dot means the field name appears in the schema; rows can still leave it empty.

Field dictionary: the exact keys

The same core field has a different key in each Actor's output. Map these before you merge datasets; a dash means the published schema has no matching key. Need a field that is not listed here, such as email? Search every Glassdoor Actor by field.

Download this comparison: CSV · JSON (every tool with a published schema, matching keys per core field, price and score).

All 11 tools, scored

Catalogue Actors link to their detail pages; the score (0 to 100) is the published formula, identical for every tool. Other Store tools follow in their own table, for reference. Price is the published primary-result rate per 1,000 (the Free-plan rate where the price is tiered; higher Apify plans pay less); start events and platform usage are excluded.

Other Store tools, for reference

Scored with the same published formula and listed for comparison only; this site does not link or recommend them.

What to check before you choose

Teams use Glassdoor data to study employee feedback, compare employer perceptions and research vacancies and compensation. Reviews and job listings answer different questions, so they should remain distinct during analysis.

Choose a review export for pros, cons and employee ratings, or a job-listing route for openings and salary estimates. Research into interviews or separate salary reports needs a tool whose documented output explicitly covers that material.

Checklist

• Distinguish ratingOverall from companyRating. Confirm which describes the review and which describes the employer before aggregating either field.
• For compensation research, inspect salary_min, salary_median, salary_max, salaryCurrency, salaryPeriod and salarySource together.
• For repeat review collection, check reviewUrl, reviewDate and the documented meaning of changed, firstSeenAt and lastChangedAt. Collection history should remain separate from the review's publication date.

Where the data is incomplete

The detailed schemas cover employee reviews and job listings.

The review tool's title mentions replies, but its listed fields do not include a reply field.

Official API route

Terms and personal data

Use aggregate business data and review Glassdoor's terms before collecting or reusing review and salary material containing personal opinions. This is general information, not legal advice.

Read Glassdoor's terms. Keep to public data, do not bypass logins or access controls, and check whether personal data is involved before you collect it. The can-I-scrape checklist walks through it.

How to start

1. Open the recommended tool in the comparison and confirm whether its documented output covers reviews, jobs or the other Glassdoor material you need.
2. Use its supported inputs to select a narrow employer or vacancy scope, checking any available location settings.
3. Start the collection and inspect company identifiers, rating context and source links before combining or summarising the records.

Call Glassdoor Job Listings Salary & Rating Scraper from code

The example input uses the Actor's published defaults; set your own Glassdoor query before you run it. You need an Apify API token.

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run_input = {
    "mode": "search",
    "searchQueries": [
        "software engineer"
    ],
    "location": "New York, NY",
    "country": "united-states",
    "startUrls": [],
    "jobIds": [],
    "employmentType": "all",
    "seniority": "all",
    "minRating": "0.0",
    "easyApplyOnly": False,
    "remoteOnly": False,
    "companySize": "any",
    "industry": "any",
    "jobFunction": "any",
    "sortBy": "relevance",
    "maxItems": 3,
    "includeDetails": False,
    "maximizeCoverage": False
}

run = client.actor("vexaloom-labs/glassdoor-job-listings-salary-and-rating-scraper").call(run_input=run_input)
if run is None:
    raise RuntimeError("The Actor run was not found.")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "<YOUR_APIFY_TOKEN>" });
const input = {
    "mode": "search",
    "searchQueries": [
        "software engineer"
    ],
    "location": "New York, NY",
    "country": "united-states",
    "startUrls": [],
    "jobIds": [],
    "employmentType": "all",
    "seniority": "all",
    "minRating": "0.0",
    "easyApplyOnly": false,
    "remoteOnly": false,
    "companySize": "any",
    "industry": "any",
    "jobFunction": "any",
    "sortBy": "relevance",
    "maxItems": 3,
    "includeDetails": false,
    "maximizeCoverage": false
};

const run = await client.actor("vexaloom-labs/glassdoor-job-listings-salary-and-rating-scraper").call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

curl -X POST "https://api.apify.com/v2/actors/vexaloom-labs~glassdoor-job-listings-salary-and-rating-scraper/run-sync-get-dataset-items"   -H "Authorization: Bearer $APIFY_TOKEN"   -H "Content-Type: application/json"   -d '{"mode":"search","searchQueries":["software engineer"],"location":"New York, NY","country":"united-states","startUrls":[],"jobIds":[],"employmentType":"all","seniority":"all","minRating":"0.0","easyApplyOnly":false,"remoteOnly":false,"companySize":"any","industry":"any","jobFunction":"any","sortBy":"relevance","maxItems":3,"includeDetails":false,"maximizeCoverage":false}'

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=vexaloom-labs/glassdoor-job-listings-salary-and-rating-scraper",
      "headers": {
        "Authorization": "Bearer <YOUR_APIFY_TOKEN>"
      }
    }
  }
}

Questions people ask

More on Glassdoor

• Error fix403 Forbidden with cf-mitigated: challenge: Cloudflare blocks
• Topic groupJobs and hiring data: every website compared
• ToolWhich Glassdoor route fits your job?
• ToolGlassdoor cost by Apify plan, rows and runs

Related websites

• Indeed2 Actors
• LinkedIn Jobs1 Actor

Sources

• Glassdoor Job Listings Salary & Rating Scraper on Apify Store
• Glassdoor Review Export - Ratings, Pros, Cons & Replies on Apify Store
• No public API documentation
• Glassdoor terms