Best Social Media Scrapers in 2026: 75,000+ Requests Benchmarked
We executed 75,000+ test requests across X, Instagram, LinkedIn, and Facebook to find the most reliable social media scraping API.
Whether you need social media data scraping for business information extraction or a high-scale social media scraping solution, our benchmark reveals the top performers.
Key performance findings
Success rate performance (Decodo):
In our tests, Decodo achieved a 91.2% success rate, the highest among the vendors tested. This makes it suitable for business information extraction from social media profiles, where minimizing retries is critical. Its average response time was 24 seconds.
Performance balance (Bright Data):
Positioned in the most efficient quadrant of our benchmark, Bright Data maintained an 88% success rate with a significantly lower average response time of 8 seconds.
Latency-optimized results (Nimble):
Nimble recorded the shortest response time, averaging 6.2 seconds. While its success rate was lower than that of the top two performers, it remains a viable option for speed-sensitive requirements.
Platform-specific success rates (Apify):
Apify performed reliably across Facebook and Instagram in our cookie-less testing environment. However, our benchmark shows that its success rates for TikTok and LinkedIn Posts fell below the 90% threshold in standardized conditions.
Social media performance benchmark
Estimating your scraping costs
Social media scraping calculator:
Use the tool below to estimate your monthly budget based on your specific volume requirements for LinkedIn, Twitter, TikTok, and Instagram.
Cost-efficiency: Requests per dollar
To find the best value, we analyzed “Requests per $.” A higher curve on the graph indicates a lower cost per lead:
Why scaling matters:
- High-volume advantage: As shown in our LinkedIn and Twitter charts, Bright Data becomes increasingly cost-effective as you scale. Beyond 1M requests, it provides nearly twice as many data points per dollar as competitors.
- Low-volume choice: For smaller projects or specific tasks, such as LinkedIn or Apify, Apify remains highly competitive under the 100k-request threshold.
Best social media scraping tools
Bright Data is a large-scale data infrastructure provider. Our testing placed it in the “Most Attractive” quadrant of our performance benchmark.
Performance: It maintained an 88% success rate with an average response time of 8 seconds.
Cost efficiency: According to our data, Bright Data is the most scalable. For both Twitter and LinkedIn extraction, cost-efficiency increases significantly when the monthly volume exceeds 1 million requests.
- Pros: Most consistent ROI for high-volume enterprise projects; comprehensive documentation and infrastructure.
- Cons: Higher entry-level pricing ($499/mo) compared to other providers in this review.
Best for: High-volume web scraping social media projects where balancing speed and reliability is a priority.
Decodo focuses on high-fidelity data extraction, prioritizing completeness over delivery speed.
Performance: It achieved the highest success rate in our benchmark at 91.2%. However, this reliability comes at the cost of higher latency, averaging 24 seconds.
Cost efficiency: While pricing is competitive for its reliability tier, it can be selected for projects where the cost of a “failed request” or retry is high.
- Pros: Industry-leading success rate for business information extraction from complex profiles.
- Cons: Longest measured latency, making it less suitable for real-time monitoring applications.
Best for: Mission-critical social media data scraping where data integrity on the first attempt is the primary requirement.
Apify operates as a platform for cloud-based scraping “Actors.” Our data show that its performance and cost-efficiency depend heavily on the specific scraping task.
Performance: While stable on Instagram and Facebook, Apify’s success rates for TikTok and LinkedIn Posts fell below our 90% threshold in baseline tests (without cookies).
Cost efficiency: Our data indicates a significant advantage for LinkedIn extraction. At volumes exceeding 1 million requests, Apify became the most cost-effective option for this subcategory. However, it was less efficient for Twitter at similar scales.
- Pros: Low entry cost ($29/mo); highly efficient for job-related data extraction.
- Cons: Variable performance across different social platforms; requires more customization to match the success rates of top-tier providers.
Best For: Small-to-medium-sized projects or specialized social media scraping tasks like recruitment data and job board monitoring.
Nimble provides an automated infrastructure designed for ease of integration and high-speed data delivery.
Performance: Recorded the shortest response time at an average of 6.2 seconds. Its success rate stabilized at approximately 72% during our standardized testing.
Cost efficiency: For Twitter and LinkedIn profile extraction, it offers a consistent cost-per-request that sits between the enterprise and entry-level tiers.
- Pros: Lowest latency in the benchmark; simplified API setup for developers.
- Cons: Requires a higher retry frequency than Bright Data or Decodo due to a lower measured success rate.
Best for: Applications requiring near-real-time data delivery where the speed of information outweighs the need for a 90%+ success rate on the first request.
Social media web Scraping with Python & APIs
Major social media platforms use distinct defensive measures, such as Instagram’s TLS fingerprinting and TikTok’s evolving U.S. data architecture, which demand specialized automation strategies.
To choose the right approach, you can follow our platform-specific deep dives and Python tutorials:
- Instagram scraping: Instagram is among the most difficult platforms to scrape due to IP reputation checks. This guide evaluates how to use scraper APIs vs. custom Python scripts to bypass these blocks.
- TikTok scraping: Learn how to navigate the TikTok Shop data ecosystem and handle device-integrity fingerprinting. Our benchmark identifies the best tools for extracting comments and search results at scale.
- Facebook (Meta) scraping: Use our Python tutorial to collect public posts, comments, and shares. We compare managed APIs like Apify and Nimble to find the best balance for Meta’s data structures.
- Twitter (X) scraping: We benchmarked top Twitter scrapers across 400 requests to identify the highest success rates for enterprise-level profile and post data extraction.
Legal & ethical guidelines: Social media scraping policies
In 2026, TikTok USDS Joint Venture LLC was officially formed in compliance with U.S. regulatory requirements. 1
In early 2026, landmark court rulings (Meta/X vs. Bright Data) confirmed that scraping public data without logging in is legal and does not break contract rules. However, if you use scraped data to train AI models, you now need to meet stricter disclosure standards to help support the publishing ecosystem.
Public data is available, but scraping data that requires logging in carries serious legal risks. Use ethical rate-limiting to keep platforms stable.
Data privacy & risk: The dangers of social media data extraction
- As Generative Engine Optimization (GEO) becomes more common, how you extract data matters. If your scraping is too aggressive or messy, major AI search engines might shadowban your brand or mark it unsafe.
- Basic proxies do not work anymore. Modern platforms use TLS fingerprinting, so you need specialized tools like MCP servers to keep a human-like profile and avoid permanent blacklisting.
Social media scraping benchmark methodology
For each provider, the success rate was calculated based on the ratio of successful responses to total requests.
The average response time was computed for each provider using the response times of successful requests. Failed or timed-out requests were excluded from response time calculations to avoid skewing latency metrics and ensure data accuracy.
75,000+ requests were executed during the measurement period across X, YouTube, Instagram, Facebook, and LinkedIn.
- x.com profile and post
- tiktok.com profile, post, and discover
- LinkedIn.com profile and post
- instagram.com profile and post
- facebook.com post and group
During our work, we did not log in to any of these websites and scraped publicly available data. Any PII identified in the results was deleted after they were downloaded.
For parts of our methodology that every web scraping API follows, see our benchmark on web scraping APIs.
See the social media APIs that each web data infrastructure provider offers:
** These scrapers exist, but their success rate was below our threshold (>90%).
*** Requires cookies. Other providers did not have this requirement. We excluded this scraper from testing since we completed all our web scraping tests without cookies.
FAQs about social media scraping
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Hi Gulbahar, Thank you for this informative article. I was wondering if FB private group's scrapping is legal or not. Do we need to take permission for that? I am doing it for my thesis and obviously not planning to sell this data. Thank you already for answering.
Hi Bashir, this is not legal advice, please consult a lawyer regarding your specific case. It is important to respect privacy and adhere to legal guidelines when handling personal information, scraping personal information would likely be illegal in most jurisdictions.