Best Apify Alternatives in 2026: How to Pick the Right Replacement

The right Apify alternative depends on which limit pushed you off the platform. We compared the options on one question: after you switch, what work still lands on your team? That test sorts the field faster than a feature checklist, because cost forecasting, Actor maintenance, output format, and deployment control are four different problems, and each one points to a different category of replacement.

At the category level, the answer looks like this:

• Requests getting blocked while your extraction logic is fine: proxy and unblocking infrastructure, such as Bright Data, Oxylabs, or ScraperAPI.

• Routine collection with no engineering capacity behind it: no-code and visual scrapers like Octoparse, Browse AI, or ParseHub.

• Site content feeding retrieval or AI workflows: crawl and extraction APIs built for language models, such as Firecrawl, Diffbot, or Crawl4AI.

• A need for deployment control and extensibility: open-source frameworks like Scrapy or Apache Nutch, on infrastructure you own.

• Recurring business data and limited capacity to operate anything: fully managed collection.

At Ficstar, a fully managed web scraping and data collection company, we process more than a billion product prices every month for over 200 enterprise customers. Teams that come to us after running a platform tend to describe the same breaking point. The scraping worked. Keeping it working became somebody's job.

There is a specific reason this question comes up more in 2026. Apify's rental Actor pricing model ends on October 1, 2026, which changes how some marketplace Actors are priced and who has an incentive to maintain them. Below is what each category of alternative changes, what a switch costs in total, and when staying on Apify is the better call.

Why teams look for an Apify alternative

The complaints that drive this search are consistent, and they are worth separating because they have different fixes. They also come from a user base that is broadly satisfied. Apify scores 8.9 out of 10 on TrustRadius and 4.7 out of 5 on G2. These are the frustrations of people who mostly stayed.

Costs that are hard to predict before a run

Apify bills compute in compute units, and one compute unit is 1 GB of allocated memory running for one hour. Four GB allocated for fifteen minutes consumes one unit. That measures memory over time, not records delivered, so two runs that return the same business result can cost different amounts. Apify's documentation states that the cost of a run depends on compute consumption, storage, proxies, data transfer, and the number of retries after failed requests.

That is the root of the most common complaint. TrustRadius published an insight panel on July 25, 2026, built from 83 verified reviews over the preceding 18 months. In it, 34% of reviewers described the pricing model as unpredictable and lacking transparency, while 55% praised how the platform handles complex extraction. Reviewers on G2 describe the same thing from the agency side, where a scraper's compute consumption cannot be predicted before it runs and the work is billable to a client.

One fair counterpoint belongs here. Spend can be capped. Apify documents a configurable usage limit and overage notifications, and free plans stop at the limit. The defensible criticism is forecasting difficulty rather than an absence of controls, though a cap protects the budget by interrupting delivery, which is its own problem for a production feed.

Actors that break when a target site changes

The second pattern has nothing to do with uptime. The job runs, and the dataset is wrong. Reviewers describe marketplace Actors whose configured parameters stop behaving consistently, and community Actors that degrade when the target site changes layout or identifiers.

The mechanism is not mysterious. Extraction depends on selectors that point at specific elements in a page, and redesigns, A/B tests, and renamed identifiers all move those elements. What no credible source establishes is a universal breakage rate, so be skeptical of anyone selling you one.

For an enterprise team, the question worth asking is who notices when a source changes, and how fast. Our answer at Ficstar is to watch the source sites continuously and update crawlers before a change reaches delivery, which is why our clients generally do not report breakage. They do not see gaps to report. That work exists on every model. The choice is whether it sits with your team or with someone under contract to do it.

Output that does not fit an AI pipeline

A newer group of teams is not looking for a scraping platform at all. They want clean, token-efficient page text for retrieval and model workflows, which is a narrower job than general-purpose extraction. Be precise about what gets solved here. Markdown, syntactically valid JSON, and business-valid records are three different deliverables. A payload can parse perfectly and still carry the wrong price, a stale timestamp, or a missing pack size.

What changed in Apify's pricing in 2026

Apify is retiring the rental model that let Actor developers charge a fixed monthly fee. According to Apify's documentation, developers could no longer publish new rental Actors or change pricing on existing ones as of April 1, 2026, and on October 1, 2026 rental Actors are fully retired, with anything not migrated converting to pay-per-usage. Apify's own migration post calls September 30, 2026 the hard deadline.

The distinction matters for buyers. An unmigrated rental Actor does not become a paid pay-per-event Actor. It converts to pay-per-usage and earns its developer nothing, which changes the incentive to keep maintaining it.

Apify has been direct about why. In its April 14, 2026 announcement, the company reported that 73% of surveyed customers preferred pay-per-event over fixed rentals, and described customers struggling with a split cost structure of a fixed developer fee plus platform usage that made total cost hard to predict. That is a vendor survey reported by the vendor, and it is also the platform documenting the exact problem its critics name.

For developers, the published pay-per-event formula is 80% of event revenue minus platform costs. Apify's 20% is a share of developer revenue rather than a line item on an enterprise invoice, so do not budget for it as a surcharge.

Pay-per-event is a genuine improvement in predictability for many workloads. Two things still deserve a check before you assume a stable bill. Most pay-per-event Actors fold platform usage into the event price, but some charge for it separately, and that appears on the Actor's page rather than in a global policy. Apify also gives 14 days' notice on price increases, applies decreases immediately, and has acknowledged that heavy former rental users may end up paying more.

The main Apify alternatives, by category

Names first, since that is what people come for. We group them by the constraint they solve rather than ranking them one through ten, because a proxy network and a no-code scraper are not competing for the same job.

Category	Examples	What it solves	What your team still owns
Proxy and unblocking infrastructure	Bright Data, Oxylabs, ScraperAPI, ScrapingBee	Access failures when extraction logic already works	Extraction correctness, retries, normalization, monitoring
No-code and visual scrapers	Octoparse, ParseHub, Browse AI, WebScraper.io, Mozenda, Thunderbit	Routine collection without programming capacity	Configuration, response to source changes, completeness checks
AI-oriented crawl and extraction APIs	Firecrawl, Diffbot, Crawl4AI	Clean page content for retrieval and model workflows	Navigation coverage, provenance, schema accuracy, delivery
Open-source frameworks	Scrapy, Apache Nutch, headless browser libraries	Deployment control and extensibility	Hosting, engineering, access handling, security, observability
Managed collection services	Ficstar, Zyte, PromptCloud, Grepsr, Import.io, DataHen	Recurring delivery of business-ready data	Requirements, acceptance criteria, vendor governance

Proxy and unblocking infrastructure

This category, which includes Bright Data, Oxylabs, ScraperAPI, and ScrapingBee, fixes the request path. If your parser is correct and your requests are being refused, better rotation and unblocking will help. If your parser is fine and your fields are wrong, it will not, because access and correctness are different layers. Cloudflare's own documentation describes detection engines that combine signatures, JavaScript signals, and machine learning, with headers, session characteristics, and browser signals feeding the classification. That is why changing proxy vendors alone often fails to resolve an access problem.

No-code and visual scrapers

Tools like Octoparse, Browse AI, and ParseHub lower the programming barrier for routine collection, which is a genuine answer to a skills constraint. They do not remove source dependence. Somebody still owns setup, the response when a site changes, and the check that a run returned everything it was supposed to. Compare quoted task, run, row, and concurrency limits closely, since that is where the ceiling sits. When the fields or the sources you need fall outside what any off-the-shelf tool covers, custom data collection is usually the shorter path than bending a template around the gap.

AI-oriented crawl and extraction APIs

Firecrawl, Diffbot, and Crawl4AI are built for one job: turning site content into something a model can use. Crawling a site to reach the right pages is a separate problem from extracting one page cleanly, and this category is aimed squarely at the second. They are a reasonable fit for retrieval. They are a weaker fit for recurring competitive pricing, which also needs product identifiers, currency, pack size, source URL, collection timestamp, and validation before anyone should price against it.

Open-source frameworks

This is the honest case for owning the stack. A framework like Scrapy or Nutch gives you full control and no license fee. The Apache Software Foundation documents Nutch's extensibility and its integration with systems like Hadoop, Tika, and Solr. A free license is not a free system, though, and that is the part to be careful about. Hosting, maintenance, access handling, monitoring, and business integration all stay with you, and those are the expensive lines.

Managed collection services

Here the unit of comparison changes from software to a contract. What you are buying is accountability for delivering usable data and repairing failures, and what you get depends entirely on what the scope and acceptance terms say. More on how to evaluate that below. If you are weighing providers more broadly than Apify, we maintain a longer overview of the best web scraping companies.

The total cost of an Apify alternative

The subscription line is the smallest part of this. Start with how the platform meters, then add what your team spends around it.

On Apify, the plan fee is prepaid platform usage rather than a license. The same balance is drawn down by compute, proxy, storage operations, and data transfer, and unused usage does not roll over at the end of a billing cycle. As of September 20, 2026, Apify's published plans are:

Plan	Monthly	Included usage	Compute unit rate	Residential proxy per GB	Max RAM
Free	$0	$5	$0.20	$8	16 GB
Starter	$19	$19	$0.20	$8	64 GB
Scale	$199	$199	$0.16	$7.50	256 GB
Business	$999	$999	$0.13	$7	512 GB
Enterprise	Custom	Custom	Custom	Custom	Custom

Apify lists SERP proxy from $2.50 down to $1.70 per thousand requests depending on plan, and external data transfer at $0.20 per GB. Proxy, storage, and transfer all run on separate meters against the same budget, and the arithmetic gets interesting quickly. At the Starter rate, 100 GB of residential bandwidth in a month consumes $800 of platform usage against $19 of included credit. That 100 GB is an assumed volume for illustration, not a typical bill. Your number comes from your own traffic.

Then add labor. The U.S. Bureau of Labor Statistics reports a median annual wage for software developers of $135,980 as of May 2025, which works out to roughly $65 an hour before benefits, employer taxes, or overhead. At that rate, 20 hours of maintenance a month is about $1,300 and 40 hours is about $2,600. Those hour counts are assumptions rather than measurements, so pull your own from ticket history.

Then add the cost of data that quietly went wrong. In a 2022 survey of more than 300 data professionals conducted by Wakefield Research for Monte Carlo, respondents reported spending 40% of their time evaluating or checking data quality, and said poor data quality affected 26% of company revenue. That survey is vendor-commissioned, four years old, and about data quality in general rather than scraper maintenance, so use it directionally.

Gartner's 2020 research put the average annual cost of poor data quality to an organization at $12.9 million, also a cross-industry figure that says nothing about collection method. Neither number is your number. Both are reasons to calculate yours.

A comparison that holds up collects six things per option:

• Subscription commitment, and the usage it already includes

• Usage above that credit, by meter

• Separately billed bandwidth, storage operations, and transfer

• Internal hours for maintenance, exception handling, and QA

• Integration and normalization work before the data is usable

• Measured incident and rework cost, including decisions made on bad records

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Watch for two accounting traps. Where the plan fee is itself usable credit, do not add the fee on top of the usage it covers. Where a pay-per-event price bundles platform resources, do not count those resources twice. We walk through the full model in our guide to how much web scraping costs.

When staying with Apify makes sense

Plenty of teams should not switch, and a guide that pretends otherwise is not much use.

Apify's site advertises more than 50,000 Actors, and when one fits your target site, you are collecting in minutes instead of building for weeks. Reviewers consistently praise the scheduling, run history, logs, retries, and automatic handling of proxy rotation. Staying is usually the right call when:

• You pull from many different sites occasionally and the marketplace already covers most of them

• You are prototyping, running a one-off pull, or testing a low-volume idea

• Your compute and proxy consumption is small enough that forecasting is not the issue

• You have developers who want direct control and the capacity to use it

Pay-per-event also addresses the split-cost problem directly for many workloads. And a strict "platform means do it yourself, service means managed" split is inaccurate. Apify's pricing page advertises custom scraping solutions, a dedicated team of experts, and SLAs with guaranteed data on its Enterprise tier. Compare the scope, accountability, and remedies written into the proposals in front of you. The brand category tells you less than the contract does.

One gap before you decide. No credible controlled study compares equivalent platform and managed workloads on cost, latency, or accuracy. Anyone quoting you a universal savings percentage is quoting marketing.

The fully managed option, and what to demand from it

This one answers a different question. Instead of choosing which platform to operate, you decide whether to operate one at all. The deliverable becomes data that meets an agreed specification, and the work of getting there, including the repairs, sits with the provider.

That only holds if the contract says so. Before signing with any managed provider, including us, get specific about:

• Source coverage and the exact fields per source

• Freshness and delivery timing, with thresholds per source

• Required-field completeness, duplicate rate, and value accuracy, with defined denominators and sampling

• Who repairs and re-delivers a failed batch, and how fast

• Escalation hours, evidence retention, and exit support

• Subprocessors, access controls, retention and deletion, and permitted reuse

Here is how we approach it at Ficstar, a fully managed web scraping and data collection company. We have been collecting web data since 2005, starting with NASA as our first client, and we now work with more than 200 enterprise customers including Fortune 500 organizations. Complex projects go through 50 or more quality checks before delivery. When we find a problem we rerun the entire collection rather than patching the output, which sometimes means our team spends a weekend on a batch you never hear about. Our crawlers are updated ahead of site changes rather than after them. Pricing is premium and quoted per project, since scope, source count, field count, frequency, and complexity all move it.

For pricing teams, that stability is the whole product. As Jorge Diaz, Pricing Manager at Advance Auto Parts, put it: "We have nationwide and local competitors with different pricing strategies. We used to struggle shopping for competitor prices as we need their data to keep our pricing competitive. Ficstar has offered us a great solution for our competitor price data needs. Now we can catch up all the price changes from our competitors no matter how they make the changes. Ficstar's data service is super reliable. We're absolutely happy with them." That work runs through our competitor price data service, and the same model covers broader enterprise web scraping programs.

Managed delivery has its own friction, and you should plan for it. Onboarding takes longer than spinning up an Actor, because specifications need to be pinned down before collection starts. Scope boundaries and change requests come up. And outsourcing collection does not outsource governance. You still define requirements, vet the supplier, and decide what lawful use looks like for your organization.

Compliance does not change when you change tools

Switching vendors does not reset your obligations. Three points are worth keeping straight.

Public pages sit on better legal footing than anything behind a login. hiQ Labs v. LinkedIn settled that the hard way when a court held LinkedIn's user agreement enforceable against scraping, and the case ended in a $500,000 consent judgment in December 2022.

Terms of service bind as contract regardless of what a page's robots.txt says. RFC 9309, the IETF standard for the Robots Exclusion Protocol, states plainly that its rules are not a form of access authorization.

The law is still moving. In Amazon.com Services, LLC v. Perplexity AI, Inc., decided August 4, 2026, the Ninth Circuit vacated a preliminary injunction against Perplexity, reasoning that on that record the user, not the AI provider, was the one accessing the site. The court tied the holding to that specific architecture, a user's own browser talking to Amazon's servers, so it says little about bulk server-side collection.

Frequently asked questions

Is Apify shutting down?

No. Apify is retiring one pricing model, not the platform. Rental Actors are replaced by pay-per-event and pay-per-usage pricing, with the final cutover on October 1, 2026.

What is replacing Apify's rental Actors?

Pay-per-event pricing, where an Actor charges for defined events such as a run starting or an item being written to the dataset. Rental Actors that are not migrated convert to pay-per-usage, where the developer charges nothing on top and you pay platform usage only.

How much does Apify cost per month in 2026?

Published plans run $19 for Starter, $199 for Scale, and $999 for Business, with Enterprise quoted custom. Each fee is prepaid platform usage rather than a license, so heavy proxy or compute consumption is billed against it and then beyond it.

What is an Apify compute unit?

One compute unit is 1 GB of allocated memory running for one hour. It measures resources consumed rather than records delivered, which is why identical business requests can produce different bills.

Do unused Apify credits roll over?

No. Apify's pricing FAQ states that unused platform usage expires at the end of the billing cycle. Unused usage does carry to the new plan on a downgrade, which is a separate case from ordinary monthly expiry.

Which Apify alternative is best for AI and RAG pipelines?

Crawl and extraction APIs built for language models, such as Firecrawl, Diffbot, or Crawl4AI, are the closest fit when you need clean page content for retrieval. They are a weaker fit for recurring pricing or inventory feeds, which need validated fields rather than readable text.

Which Apify alternative works without a developer?

No-code and visual scrapers like Octoparse, Browse AI, or ParseHub cover routine collection without programming. If the data feeds a production process and nobody on the team can own exceptions when a source changes, a managed service is the more realistic option.

Which Apify alternative is best for competitor price monitoring?

Usually a managed collection service rather than a platform. Recurring price feeds need matched product identifiers, currency, pack size, a collection timestamp, and validation before anyone prices against the data, and that work has to happen on somebody's schedule every day the feed runs. Our tire retailer case study shows the shape of it: 20 competitors, more than 50,000 SKUs, about a million pricing rows per weekly crawl.

Start Your Free Trial

Pick the category that matches the constraint that pushed you off the platform, then test it against your real sources before committing to anything. That is what our free trial is for. We collect live data from the sites you care about, in the fields and the format you need, typically two weeks, and up to three months for complex projects, and you judge the output before a contract exists. Our work is backed by a 100% satisfaction guarantee.

Start your free trial and tell us which sources broke first.