Zenrows vs Apify Benchmark

Reproducible benchmark comparing Zenrows and Apify across 7 targets, run in June 2026.

Companion code for the Zenrows article Best Apify Alternative for Large-Scale Scraping.

What this tests

#	Target	Type	Zenrows score	Apify score
1	walmart.com product page	Protected	100	7.5
2	glassdoor.com company page	Protected	99.5	11
3	bayut.com property search	Protected	100	35
4	google.com SERP	Protected	95	79
5	ikea.com product page	Protected	100	2.5
6	news.ycombinator.com	Unprotected	100	99.5
7	docs.scrapy.org	Static documentation	100	64.5

200 requests per target per tool. 2 requests/second. Concurrency: 2.

What is recorded per request

• HTTP status code (200 = success)
• Response time in milliseconds
• Whether the returned HTML contains a valid <title> tag

Actor used for Apify

apify/playwright-scraper — the most widely used general-purpose Playwright Actor on the Apify Store.

What this benchmark does NOT cover

• Apify's pre-built marketplace Actors for specific sites (Instagram, Google Maps, LinkedIn). The test uses a general-purpose Actor only.
• Apify's scheduling, dataset storage, and monitoring features.
• Zenrows' Scraping Browser in a multi-step session workflow.

Test date

19th June 2026. Rerun results may differ as sites update their anti-bot configurations.

Setup

Prerequisites

• Python 3.10+
• A Zenrows API key
• An Apify API token

1. Clone the repository

git clone https://github.com/ZenRows/zenrows-vs-apify-benchmark.git
cd zenrows-vs-apify-benchmark

2. Create a virtual environment

python -m venv .venv
source .venv/bin/activate   # macOS/Linux
.venv\Scripts\activate      # Windows

3. Install dependencies

pip install -r requirements.txt

4. Configure credentials

export ZENROWS_API_KEY=your_zenrows_api_key
export APIFY_API_TOKEN=your_apify_api_token

Running the benchmark

python run_benchmark.py

Output

Raw per-request results are written to results/raw_<tool>_<timestamp>.csv. The aggregated results used in the article are committed as Zenrowsresults.csv and apify_results.csv.

License

MIT