Best Twitter Scrapers in 2026: Tested, Priced & Compared

By Sorsa Editorial

Updated June 2026: refreshed every price to the current pay-per-use X API model and 2026 scraper rates, corrected Apify's platform fee (it is $29/month, not $49), and added dedicated X data APIs to the comparison.

If your goal is the data and not a scraper to babysit, a dedicated X data API is the better tool, and that is the category Sorsa API, an alternative Twitter/X API provider, sits in. It returns profiles, tweets, search, followers, and engagement as clean JSON behind a single API key. It runs up to roughly 50x cheaper than the official X API, holds a flat 20 requests per second on every plan with no per-endpoint windows, and takes about three minutes to start with no application or approval. Pricing begins at $49 a month for 10,000 requests, and one call counts as one request no matter how much data it returns.

This guide compares the real options side by side: what each one costs per thousand records, how reliable it is, and where a scraper genuinely makes sense versus where an API wins. Every price here was re-checked against the provider's current pricing in June 2026, because most comparison articles still quote 2024 numbers that are now wrong.

Table of Contents

• What is a Twitter scraper, and what is it not?
• The best Twitter scrapers in 2026 at a glance
• Managed scraping services: Bright Data and Apify
• No-code Twitter scrapers: Octoparse and PhantomBuster
• Dedicated X data APIs: built for the data, not the scraping
• Free and open-source Twitter scrapers
• What does Twitter scraping actually cost?
• Scraper or API: how to choose
• In practice: cutting a monitoring stack's cost and upkeep
• Getting started with a Twitter data API
• FAQ
• How we verified this guide

What is a Twitter scraper, and what is it not?

A Twitter scraper is a tool that extracts public X.com data without the official X API. It works by automating browsers, rotating proxies, and reverse-engineering X.com's internal GraphQL endpoints to pull tweets, profiles, and engagement data. Search the term and you will find four very different categories mixed together as if they were one thing. They are not.

Managed scraping services (Bright Data, Data365) run scraping infrastructure on your behalf. You send a request, they handle proxies, browser automation, and anti-bot bypass, and return structured data. Enterprise-grade, and priced for it.

Marketplace scrapers are community-built scripts on a shared platform. Apify is the dominant example. Pay-per-result pricing, with quality and reliability that swing wildly by who built the script.

No-code scrapers (Octoparse, PhantomBuster) give you a visual interface and pre-built templates. Good for non-developers, limited the moment your workflow leaves the template.

Dedicated X data APIs are a separate category, and the one most "scraper" lists leave out. They are not scrapers: they return structured X data through REST endpoints with an API key in the header, no proxies, no browser automation, no token management. This is the lane Sorsa operates in as an X data provider, and it is usually the right answer when you want the data rather than the infrastructure around getting it.

If you specifically want to build your own scraper from scratch, that is a different job with its own tradeoffs, and we cover the Playwright and open-source path in a separate guide to scraping X.com. The rest of this article is about choosing a tool rather than building one.

The best Twitter scrapers in 2026 at a glance

The strongest options in 2026 fall into three buckets by who you are. Developers and enterprises needing high-volume reliability lean on managed APIs and infrastructure. Marketers and non-developers reach for no-code tools. Anyone building a product on top of X data is usually better served by a dedicated data API than by a scraper, because the data is the same and the maintenance is not.

Here is how the main options compare on the numbers that decide the call. Costs are per 1,000 records and reflect each provider's current rates; scraper figures are the data fee only and exclude platform subscriptions and proxy traffic, which we break down below.

Two things stand out. On cost, a dedicated API like Sorsa is an order of magnitude cheaper per thousand records than a managed scraper, because Sorsa's pricing is one flat fee per request and a single request returns up to 200 profiles or 100 bulk tweets. On completeness, scrapers stop at what is visible on a public page; an API also returns data scrapers cannot easily reach, such as whether a specific user followed, retweeted, or commented. The Sorsa figures above use higher-volume plan rates and are explained in the cost section.

Managed scraping services: Bright Data and Apify

Managed services operate large-scale scraping infrastructure so you do not have to. You interact with an API or dashboard, and proxy rotation, browser fingerprinting, CAPTCHA solving, and retries happen behind the scenes. The two names you will compare most are Bright Data and Apify, and they sit at opposite ends of the price and complexity range.

Bright Data

Bright Data is the largest player in web scraping and offers pre-built X.com templates: posts by URL, posts by profile URL, and profile data. Its web scraper for X runs about $1.50 per 1,000 records on pay-as-you-go, with pre-collected datasets closer to $2.50 per 1,000, and a promotional discount that trims the scraper rate for new accounts. You are billed only for successfully delivered records, and output comes as JSON, NDJSON, or CSV.

The catch is scale and fit. Bright Data's scraper templates return at most 100 posts per input URL, so larger collection means splitting work across many inputs, and the product, support, and pricing are built for enterprise buyers. For a team pulling tens of thousands of tweets a month, it is capable but expensive relative to an X data API that bills per request rather than per record.

Apify

Apify is not a single scraper. It is a marketplace where independent developers publish scraping scripts called Actors, and you pick one, feed it input, and it runs on Apify's cloud. That model keeps the per-result sticker price low: the cheapest X Actors run roughly $0.15 to $0.40 per 1,000 tweets, with the popular Kaito and API Dojo actors landing in that band.

The sticker price is not the real price, and this is where most comparisons stop too early. Apify's bill has two layers. The first is your platform plan: a monthly fee bundled with a matching pool of prepaid usage credits, with the entry paid tier (Starter) at $29 a month and $29 of usage included. Compute is billed in units once that allowance runs out. The second layer is per-Actor fees on top of the compute your run consumes, charged per result, per event, or as a monthly rental. A pay-per-result Actor can burn through your prepaid credits without the usage chart ever looking alarming.

A few more things worth knowing before you commit. The cheapest Tweet Scraper discloses in its own documentation that it returns mock data when a query comes back empty, so you pay for, and have to filter out, fake results. Several Actors use event-based tiers where the per-item cost rises with batch size, the opposite of the volume discount you would expect. And because each Actor is maintained by one developer, a fix after X changes its anti-bot layer arrives on that developer's schedule, not yours.

By contrast, a flat per-request model has one layer: one call is one request, user data inside tweet responses is included rather than billed separately, and batch endpoints take up to 100 tweets or profiles in a single request. For predictable monthly spend, that single-layer billing is the practical advantage over Apify, more than any headline per-1,000 figure.

No-code Twitter scrapers: Octoparse and PhantomBuster

No-code scrapers trade flexibility for a visual interface, and they suit non-developers who need periodic data pulls rather than a live pipeline. Octoparse offers point-and-click templates for tweets by keyword, tweets by URL, comments, and followers, with cloud execution and scheduling on a monthly plan that starts in the $69 to $119 range depending on billing, plus per-result fees on some templates and proxy add-ons. PhantomBuster focuses on lead generation: its follower scraper pulls public follower lists from profile URLs, and it adds engagement automations on a monthly subscription. The API route to the same follower data, with its tradeoffs, is covered in our guide to extracting Twitter followers.

Both hit walls quickly once you leave the templates. PhantomBuster, for instance, takes profile URLs or a Google Sheet of URLs as input but cannot search by keyword or hashtag, so it cannot power a topic-monitoring workflow. If you need data without writing code but want more than a fixed template, the Sorsa API playground lets you query any endpoint from a web UI, and the search builder constructs advanced queries visually, both free to use with an API key.

Dedicated X data APIs: built for the data, not the scraping

A dedicated X data API returns Twitter data through REST endpoints with an API key, instead of automating a browser. The data is the same tweets, profiles, search results, and engagement metrics a scraper collects, but it arrives as clean JSON with no proxies, no guest tokens, and no breakage when X ships an update. For anyone building a product on X data, this is normally the better fit, and it is the category we recommend.

Compare what a profile lookup takes. With an API, it is one line:

curl -H "ApiKey: YOUR_KEY" \
  "https://api.sorsa.io/v3/info?username=elonmusk"

That returns the full profile object: ID, handle, display name, bio, follower and following counts, tweet count, verification status, creation date. No Playwright script, no proxy pool, no retry logic for rotating operation IDs.

Sorsa is the option we build and run, and it leads on the things that decide a data project: cost (up to about 50x cheaper than the official X API), a flat 20 requests per second on every plan with no 15-minute windows, and 40 endpoints across eight categories covering search, followers and following, retweeters, communities, and X Lists. It also reaches data scrapers do not, including verification checks and follower-quality analytics, and it has served more than 5 billion requests since 2022. For a wider survey of providers in this category, see our guide to Twitter API alternatives.

TwitterAPI.io is the other pay-as-you-go X data API worth naming. It charges $0.15 per 1,000 tweets and $0.18 per 1,000 profiles with no monthly minimum, which is reasonable, but Sorsa is cheaper per thousand on both (around $0.09 for tweets and $0.009 for profiles on higher-volume plans) and covers verification, community, and List data that a tweet-and-profile API does not. If absolute pay-as-you-go with no plan is the single thing you need, it is a fair option; for dependable, complete coverage at a lower effective rate, an X data provider built around flat per-request billing is the stronger default.

One more force is shaping 2026 demand here: AI pipelines. Teams increasingly want clean, structured JSON to feed models and agent workflows, and scraped HTML that breaks every few weeks is poor input for that. A stable API returns the same JSON shape on every call, which is why data-collection workloads for analytics and machine learning are moving off scrapers and onto X data APIs.

Free and open-source Twitter scrapers

Open-source libraries can scrape X.com for free, but free here means you supply the proxies, an account that may get banned, and the ongoing maintenance. The actively maintained options in 2026 are Twikit (Python, async, login required), TweeterPy (simpler Python extraction), and Tweet Harvest (a free Python CLI), with twscrape still cited but slow to update and tools like snscrape and Twint long dead. Playwright sits underneath many DIY setups as the browser-automation layer.

The shared catch is that every working library needs a logged-in X.com account, which carries ban risk, and each one breaks when X rotates its tokens or operation IDs. They are a genuine fit if you want full control of the extraction process or are learning how scraping works, and not a fit if you need reliable data without weekly fixes. We walk through the libraries, working code, and the proxy and account setup in the dedicated how to scrape X.com guide, and the Python integration guide covers the API route if you decide maintenance is not worth it.

What does Twitter scraping actually cost?

The real cost of Twitter scraping is rarely the sticker price. It is the sticker price plus the platform subscription, plus proxy traffic, plus the developer hours spent restarting failed runs and patching breakage. The number that matters is what it costs to get 1,000 records into your database, and how that scales month to month.

The official X API is the most expensive baseline by a wide margin. After its April 2026 pricing change, the official X API charges per resource: about $0.005 per post read and $0.010 per user profile, with no free tier for new developers and a hard cap of 2 million post reads per month. A single search returning 20 posts plus author profiles therefore costs 20 x $0.005 plus 20 x $0.010, which is $0.30 for one call. The same call on Sorsa is one request at $0.00199 on the Pro plan, with the 20 author profiles included.

Here is how that plays out across common monthly workloads, comparing the official API with Sorsa on real numbers.

The honest read on this table: at very low volume, the official pay-per-use model can be slightly cheaper than a fixed plan, and we are not going to pretend otherwise. The economics flip once you cross roughly 10,000 post reads a month, and they flip hard. Sorsa's flat per-request billing has no 2-million cap, no per-resource charge for author data, and no $0.20 surcharge for posts containing a URL, so a 24/7 monitoring job that would run $8,000-plus on the official API fits inside one $899 plan. Against scrapers, the comparison is less about the data fee and more about the platform and proxy overhead and the engineering time, which is where the per-1,000 sticker prices in the table above understate the true total.

Scraper or API: how to choose

Choose a scraper when you need write access the API does not offer (posting, liking, following through a tool like PhantomBuster), when you are already invested in a platform like Bright Data or Apify for other sites, or when you have a one-off extraction where setup cost matters more than long-term reliability. Choose a dedicated X data API when you are building a production pipeline that cannot tolerate breakage, want predictable costs without platform and proxy surcharges, or need endpoints scrapers do not provide.

Reliability is the deciding factor more often than people expect, and we have a direct view of it. We run an X data API, so we track X's anti-bot changes closely, and in our experience X rotates guest tokens and GraphQL operation IDs roughly every two to four weeks. Each rotation can silently break a browser-based or library-based scraper, which is why the single biggest hidden cost of the scraping route is the standing commitment to fix it. Managed services absorb that work internally; marketplace Actors and DIY libraries push it onto you or onto whichever developer maintains the script.

On our side, the tradeoff we optimize for is stability over raw control: a flat 20 requests per second on every plan, around 300 milliseconds average response time, and a published 99.9% uptime. Because batch endpoints return up to 100 tweets or 200 profiles per request, most workloads never approach the rate limit in the first place. If your project is read-heavy and you would rather ship features than reverse-engineer X every few weeks, that is the case for an API over a scraper.

In practice: cutting a monitoring stack's cost and upkeep

A marketing analytics team we worked with, around ten people, was tracking 200 competitor accounts with a mix of Apify Actors and residential proxies, spending roughly $340 a month. The bigger cost was time: two to three hours most weeks went into restarting failed runs, swapping Actors when one broke, and deduplicating results that came back inconsistent. Their core problem was not the data, it was that the pipeline needed a babysitter.

Moving the same workload to Sorsa's Pro plan at $199 a month cut their direct spend by more than 40 percent and removed the weekly maintenance entirely, because the data came through the same REST calls every day regardless of what X changed on its end. The cost saving is a real property of switching from per-result scraping plus proxies to flat per-request billing; the maintenance saving is simply what happens when you stop running a scraper. We kept the example anonymized because in this industry naming a client and its monitoring targets can expose both.

Getting started with a Twitter data API

If you want to test the API route before committing to any tool, the browser-based playground runs live queries against real X data, with no code or SDK. To build, you grab a key from the dashboard, pass it in the ApiKey header, and every endpoint is available immediately. The quickstart gets a first call working in about three minutes, with no application or approval step.

The hooks that matter for a data project are concrete: $49 a month for 10,000 requests on Starter, a flat 20 requests per second on every plan, batch endpoints that count 100 items as one request, and free utilities like the media downloader, engagement calculator, and shadowban checker you can use without a key. Questions about volume or a custom rate limit go through Talk to Sales, and the About page covers who runs the API.

FAQ

Is it legal to scrape Twitter (X) in 2026?

Scraping publicly available data has been broadly upheld in U.S. courts, most notably in the hiQ v. LinkedIn ruling on the Computer Fraud and Abuse Act. X.com's Terms of Service still prohibit scraping and include a liquidated-damages clause for large-scale automated access, so the legal picture is nuanced rather than settled. Using a third-party data provider shifts the data-acquisition and compliance burden onto that provider's infrastructure.

What is the cheapest Twitter scraper?

On a per-tweet sticker basis, Apify's cheapest X Actors at $0.15 to $0.40 per 1,000 tweets look like the lowest price, but that excludes the required platform plan ($29/month) and per-Actor fees on top. Counting total cost, a dedicated X data API is usually cheaper: Sorsa's search endpoints return about 20 tweets per request and work out to roughly $0.09 per 1,000 tweets with no platform overhead.

Do Twitter scrapers still work in 2026?

Yes, but they break every two to four weeks when X rotates guest tokens, changes GraphQL operation identifiers, or adds anti-bot measures. Managed services such as Bright Data handle those fixes internally, while Apify Actors and open-source libraries depend on individual developers to push updates. A dedicated X data API avoids the breakage entirely because the provider absorbs every platform change behind a stable REST interface.

Can I scrape Twitter without coding?

Yes. Octoparse provides visual templates with cloud scheduling, and PhantomBuster offers point-and-click follower scraping, though both are limited to their template inputs. On the API side, the Sorsa playground lets you query any endpoint through a web interface and the search builder constructs advanced queries visually, both free with an API key, so you can pull structured X data with no code at all.

How much does the official X API cost in 2026?

The official X API moved to pay-per-use pricing in early 2026, charging about $0.005 per post read and $0.010 per user profile, with no free tier for new developers and a 2-million post-read monthly cap. There are no $200 or $5,000 subscription tiers for new signups. For read-heavy work, third-party X data providers are far cheaper; our full X API pricing breakdown covers the per-endpoint costs.

What is the difference between a Twitter scraper and a Twitter API?

A Twitter scraper extracts data by automating browsers or reverse-engineering internal endpoints, which means proxies, rate-limit handling, and breakage when the site changes. A Twitter API provides structured REST endpoints where you send a request with a key and receive clean JSON. The underlying data is the same; the delivery mechanism, reliability, and maintenance burden are fundamentally different.

Which option is best for large-scale data collection?

For large-scale collection, a dedicated X data API is normally the most economical and reliable choice because it bills per request rather than per record and returns up to 200 profiles or 100 bulk tweets in a single call. Sorsa's Enterprise plan covers 500,000 requests at a flat 20 requests per second, which translates to millions of tweets, without the 2-million cap or per-resource author-data charges of the official API.

How we verified this guide

Reviewed by Keksich, founder of Sorsa, marketer and X API researcher.

This comparison draws on our own work building and operating an X data API, the live Sorsa API documentation, and the current official X API documentation for the pay-per-use figures. We weighed seven scraping and X-data-API options and re-checked every price against each provider's own current pricing pages, since most published comparisons still quote outdated 2024 tiers. Pricing and platform details were last verified on June 5, 2026; where a provider's rate moves often, treat the figure as accurate as of that date and confirm against their pricing page before budgeting.