The Apify web scraping, data extraction, and automation platform
Apify Web scraping and AI agent platformReviews from AWS customer
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Powerful Automation Agents Without the Hosting Headache
What do you like best about the product?
It’s useful for creating automation agents, especially web scrapers, which would otherwise require complex infrastructure to host and run, and that can get expensive.
What do you dislike about the product?
There are some low-quality and not very useful actors in the marketplace. I think better vetting could help remove them and maintain higher standards.
What problems is the product solving and how is that benefiting you?
In our business we have a need to collect structured data from various sources so by building actors and scrapers we are able to achieve it.
Powerful Social Media Data Scraping for Twitter and Instagram
What do you like best about the product?
Scraping data from social media platforms like Twitter and Instagram.
What do you dislike about the product?
UI and UX, its challenging for a new user
What problems is the product solving and how is that benefiting you?
Helped me complete the automation which was built around trying Outlier detection post from social media
Apify Saves Time with Intuitive Workflows and Ready-Made Actors
What do you like best about the product?
Pros:
Apify has saved me a huge amount of time. The interface is intuitive, and the ready‑made actors cover almost everything I need. I like that I can set up workflows without writing complex code.
Apify has saved me a huge amount of time. The interface is intuitive, and the ready‑made actors cover almost everything I need. I like that I can set up workflows without writing complex code.
What do you dislike about the product?
Sometimes the documentation feels a bit scattered, so it takes a moment to find the exact example I need.
Also you need to read a lot in order to chose the correct tool that most probably will help you.
Also you need to read a lot in order to chose the correct tool that most probably will help you.
What problems is the product solving and how is that benefiting you?
I’m very satisfied — the platform is stable, fast, and helps me automate tasks that used to take hours.
Apify Makes Python Scraping Easy—and Lets Me Publish Actors
What do you like best about the product?
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.
What do you dislike about the product?
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.
What problems is the product solving and how is that benefiting you?
Apify takes the burden off my plate when it comes to provisioning servers, managing browser instances, and handling failures. Its structured datasets, built-in export options, and results API make it easy to pull data and plug it straight into my backend or analysis workflow, without having to write a bunch of glue code in between.
Apify Supercharged Our Lead Generation with Automated Crawlers
What do you like best about the product?
We use Apify to run automated crawlers that gather data from multiple sources, clean and normalize the results, and export them into structured formats like CSV or JSON. This data is then integrated into our outreach and CRM workflows, where we use it for prospecting, qualification, and targeted campaigns.
Overall, Apify helps us scale our lead generation efforts, reduce manual work, and maintain a consistent pipeline of relevant prospects.
Overall, Apify helps us scale our lead generation efforts, reduce manual work, and maintain a consistent pipeline of relevant prospects.
What do you dislike about the product?
However, the platform has a noticeable learning curve, especially for non-technical users. Setting up actors, handling errors, and navigating logs can be challenging at first. The interface can also feel a bit cluttered when managing multiple tasks. So while it’s highly capable, it takes some time and experience to use it comfortably and effectively.
What problems is the product solving and how is that benefiting you?
The main business problem Apify solves for us is access to high-quality, up-to-date lead data at scale. Manually collecting this information would be extremely time-consuming and inconsistent. With Apify, we’re able to automate the extraction of key data points such as company names, product details, websites, and social profiles, which significantly improves both efficiency and accuracy.
Super Easy Competitor Social Scraping for Actionable Intelligence
What do you like best about the product?
to scrape competitors, makes analying socials of competitors, makes it super easy to get data and intelligence
What do you dislike about the product?
Prepaid credits do not roll over to the next month
What problems is the product solving and how is that benefiting you?
It converts chaotic web pages into clean text and JSON, automates the extraction of massive datasets, providing the fresh, high-quality training data, It bypasses anti-bot walls and complex site structures, serving as the "eyes" that allow AI agents to reliably fetch real-time answers
Self employee development
What do you like best about the product?
Templates and low price and nice customer service
What do you dislike about the product?
Can't delete code in source section and affiliate program it's difficult to join
What problems is the product solving and how is that benefiting you?
Google Map scraper
Apify Twitter Scraper: Unreliable Limits, Unpredictable Results, and Costly Overfetching
What do you like best about the product?
Easy to set up actors, flexible automation tools, and good integration options for scraping workflows.
What do you dislike about the product?
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.
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.
What problems is the product solving and how is that benefiting you?
We want the tweets of several profiles and it helped to scrap tweets at affordable cost
Powerful Web Data Collection Automation That Saves Time
What do you like best about the product?
The platform is a powerful way to automate web data collection, and it makes deploying scraping workflows much faster than building and maintaining custom infrastructure. It’s especially helpful when you combine scraped data with automation tools to support lead generation, research, or monitoring workflows. ≈
What do you dislike about the product?
There’s a bit of a learning curve when working with different actors, but once everything is set up, the platform runs reliably and saves me a significant amount of time.
What problems is the product solving and how is that benefiting you?
Apify has accelerated my data-driven workflows by making it straightforward to collect, store, and integrate web data into automated pipelines and broader business processes.
Powerful Features—The Google Maps Scraper Delivers Tons of Leads
What do you like best about the product?
I love the various features I can use but most importantly the Google maps scraper that has helped me scrape a ton of leads for my business
What do you dislike about the product?
I don't dislike anything about the product.
What problems is the product solving and how is that benefiting you?
Saves 100s of hours trying to get leads for my business by manually scraping Google Maps.
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