Apify Reviews & Product Details

Everything lives in one place, you pay only when it's called, and you don't have to build a single scraper.

That's the part I think is genuinely underrated about Apify - it's not just a hosting platform, it's a scraping utility layer you can lean on. For someone building a AI agentic business for other businesses that's a significant shortcut. The UI is not super complicated to use, the API integration is easy to find and implement, their hosting servers have plenty power to handle huge data outputs. Review collected by and hosted on G2.com.

The pricing model is confusing - compute units, platform fees, Actor rental fees all layered on top of each other, hard to predict costs before you run something. Free tier is quite limited, you hit the ceiling fast when experimenting. Review collected by and hosted on G2.com.

The Actor ecosystem and deployment pipeline are best-in-class. I can go from an idea to a production-ready web scraper or automation tool in under an hour, publish it to the Apify Store, and have it running immediately on managed infrastructure with built-in proxy rotation, scheduling, and storage.

The platform takes care of the painful parts of scraping at scale proxy management, browser orchestration, rate limiting, and retry logic so I can stay focused on the actual extraction logic. The pay-per-result pricing model for Store actors is a genuine differentiator: it lets me monetize the tools I build while giving users a low-friction way to try them.

The API and SDK are well-documented and consistent, and the recently added MCP server support makes it trivial to plug scrapers into AI agent workflows. I run 80+ actors and MCPs on the platform, and reliability has been solid. Review collected by and hosted on G2.com.

The build system can be frustrating — when a deployment fails, the error messages are often vague and don't point you

to the actual problem. Debugging a failed Docker build on the platform sometimes means pushing multiple

trial-and-error commits just to get a useful stack trace. The Store discovery algorithm is also opaque; it's hard to

understand why some actors rank well and others with better SEO and more users don't. Pricing transparency for

platform compute could be improved — estimating costs for a new actor before running it at scale requires a lot of

guesswork. The web IDE is underpowered compared to local development, and the dashboard UI can feel sluggish when

managing a large portfolio of actors. Minor gripe: the documentation sometimes lags behind SDK changes, so you

occasionally find examples that use deprecated patterns. Review collected by and hosted on G2.com.

I love Apify because it saves me from having to build scrapers from scratch, and I can write my scrapers in Python, which fits seamlessly into my existing workflow. I also appreciate that I can publish my own Actors to the marketplace and potentially earn from them as well. Review collected by and hosted on G2.com.

I end up paying for compute time even when a big chunk of that time is just spent waiting for slow pages to load, which feels pretty wasteful. I also can’t always rely on a third-party Actor for sensitive scraping tasks, because I don’t fully control what it’s doing behind the scenes. And for simple, small-scale scraping, it honestly feels like overkill—I’d rather just run my own script. Review collected by and hosted on G2.com.

The API is clean and the JSON output is predictable. I connect it to LLMs in minutes without fighting parsers or handling edge cases. Pre-built actors for websites, YouTube, and Spotify save hours compared to building scrapers from scratch. It just works. Review collected by and hosted on G2.com.

The dashboard UX feels clunky. Finding actors, managing runs, and navigating the platform isn't smooth. I haven't tested deep linking much yet, but it hasn't worked well when I tried. The core functionality is solid even if the interface needs polish. Review collected by and hosted on G2.com.

Easy to set up actors, flexible automation tools, and good integration options for scraping workflows. Review collected by and hosted on G2.com.

Our experience with Apify’s Twitter scraper started positively, but over time it became extremely disappointing and costly due to multiple issues that directly affected reliability and budget control.

1. Parameters not working as expected

Many of the parameters provided by the actor did not behave consistently. Even when we configured limits such as maximum items to fetch, the scraper did not always respect them. This made it very difficult to rely on the actor in a production workflow where predictable behavior is critical.

2. Unnecessary fetching that wasted our budget

On several occasions the scraper fetched thousands of tweets even though strict limits were configured. These runs consumed a large amount of resources and unexpectedly increased our costs. What made this worse was that these fetches were not intentionally triggered by us, yet the platform still charged for them. When we raised the issue, there was no meaningful resolution or refund, even though the behavior clearly went beyond the configured limits.

3. Fetching outdated tweets instead of recent ones

Another recurring issue was that the scraper frequently returned old tweets instead of the latest ones, even when using options intended to retrieve the most recent results. For time-sensitive workflows this makes the data unreliable. We often saw situations where tweets from the previous day appeared while tweets posted within the last hour were missing entirely.

4. Uncertain and inconsistent scraper behavior

The overall behavior of the Twitter scraper felt unpredictable. Identical configurations would sometimes produce completely different results between runs. Some runs would miss relevant tweets, while others would return irrelevant or outdated data. This level of inconsistency makes it difficult to trust the tool for automated systems.

While Apify provides a capable platform and a developer-friendly interface, the lack of strict control over limits, unreliable scraping results, and poor cost safeguards created serious operational issues for us. For any system that depends on predictable data collection and controlled spending, these problems can become very costly very quickly.

Until stronger safeguards, clearer parameter behavior, and better cost protection mechanisms are implemented, it is difficult to recommend relying on the Twitter scraper for production-critical workflows. Review collected by and hosted on G2.com.

What I like best about Apify is how it combines powerful, scalable web scraping with a clean, developer-friendly workflow. It lets me automate complex data pipelines—like extracting YouTube data at scale—without worrying about infrastructure or maintenance. The combination of ready-made actors, API access, and seamless integrations saves a huge amount of time while still giving me full control when I need it. Review collected by and hosted on G2.com.

Some actors need fine-tuning, and initial setup can be slightly complex for advanced workflows and scaling needs. Review collected by and hosted on G2.com.

What I like most about Apify is how flexible and reliable it is for web scraping and automation. The platform makes it easy to run ready-made Actors from the Apify Store, and at the same time, it gives you full control if you want to build custom scrapers.

I also appreciate how everything is cloud-based — scheduling, monitoring, API access, and proxy management are all handled in one place. The dashboard is clean, logs are detailed, and it’s easy to track runs and debug when needed. Once you get used to it, it becomes a very powerful tool. Review collected by and hosted on G2.com.

Nothing to dislike for me. It's an gamechanger for my use case. I automated a lot of works using Apify. Review collected by and hosted on G2.com.

The most helpful aspect of Apify is the combination of a powerful cloud infrastructure and the extensive Actor Store. It effectively handles complex anti-scraping measures like browser fingerprinting and proxy rotation automatically. Being able to deploy pre-built scrapers for major sites in minutes, rather than writing custom code for weeks, is a massive upside for our productivity. Review collected by and hosted on G2.com.

The credit-based pricing system can be somewhat difficult to predict for complex, large-scale crawls, which makes budgeting a bit of a challenge. Additionally, while the platform is incredibly powerful, the sheer number of features creates a steep learning curve for non-technical team members who just need to download a simple dataset. Review collected by and hosted on G2.com.

What I like best about Apify is how quickly I can go from idea to actual data. For things like Google Maps scraping, I don’t need to build a crawler from scratch, I can just use an existing actor, set my search keywords and locations, and start getting results in minutes.

The platform handles things like proxies, browser automation, and blocking much better than most DIY setups. I also like that the data comes out clean in JSON, CSV, or Excel, which makes it easy to use in my own tools and dashboards. Overall it saves a lot of engineering time compared to running and maintaining my own scrapers. Review collected by and hosted on G2.com.

One thing I don’t like is that the pricing can become expensive when you run scrapers at scale, especially for data-heavy sources like Google Maps where a lot of proxy and compute usage is required. If you’re running large jobs or frequent crawls, the costs add up quickly.

I also found that some actors can fail or return partial data when Google changes something, so you sometimes have to rerun jobs or tweak settings. It’s not a deal breaker, but it does mean you still need to monitor runs instead of treating it as completely hands-off. Review collected by and hosted on G2.com.

I love Apify’s interface and usability, which sets it apart from other platforms that tend to be difficult to navigate. This user-friendly design made it easy for me to get accustomed to the software right from the start. Apify has greatly simplified my ability to access lead data for my outbound outreach campaigns, specifically when scraping LinkedIn profile data. Its ease of use is invaluable, especially compared to my previous experience with other products like ScrapeNinja, which didn't perform as effectively. I also feel confident in recommending Apify to others based on its strong points, and I rate it highly due to these features. Review collected by and hosted on G2.com.

I find the API side of Apify could be improved in terms of ease of use. Integrating actors with some automation platforms like n8n can get complicated at times. Additionally, the API documentation could be simplified to make it easier for users to understand and implement. Review collected by and hosted on G2.com.