--- title: "Bright Data vs TwitterAPIs: Async Scraper vs Sync API (2026)" description: "Bright Data's Twitter Scraper API is $1.50 per 1,000 records, async via webhook. TwitterAPIs is $0.0008 per call, synchronous, no plan. Full comparison." canonical: https://www.twitterapis.com/twitterapis-vs-brightdata generator: md-live-route generated: 2026-09-29T20:30:16.343Z --- # Bright Data vs TwitterAPIs: Async Scraper vs Sync API (2026) 1. [Home](https://www.twitterapis.com/) 2. / Bright Data Comparison HEAD-TO-HEAD # TwitterAPIs vs Bright Data: Sync API, Async Scraper ## TwitterAPIs vs Bright Data: which is cheaper for Twitter data? TwitterAPIs is a pay-per-call Twitter and X data API that returns typed tweet, user and search results at $0.0008 per call, one HTTP response, up to 20 tweets, no plan required. Bright Data's Twitter Scraper API bills $1.50 per 1,000 records pay-as-you-go, or $499 a month for a plan covering 384,000 records, and delivers results asynchronously through a webhook callback or a dataset you poll rather than in the original response. Per tweet landed, TwitterAPIs runs well under Bright Data's pay-as-you-go rate; Bright Data's case is its residential proxy network spanning far more than Twitter. [Start Free](https://www.twitterapis.com/signup) ## How we source these numbers Every Bright Data figure on this page was re-verified against brightdata.com/pricing/web-scraper and their scraper documentation on 5 September 2026, not from a third-party summary. That reading confirmed the pay-as-you-go rate of $1.5 per 1,000 records, the $499/month Scale plan with 384,000 records included and $1.3 per 1,000 after that, the free tier of 5,000 records a month with no card, and the policy of charging only for successful deliveries. The request modes, the delivery options and the SDK list in the sections below come from the same reading. Our own rates come from our public pricing page. Pricing pages change: if you are reading this months later, check both before you commit to either. Per our own spec, 24 of 109 endpoints are free and 62 cost $0.0008, with the remaining 23 between $0.0016 and $0.01. Each price is published inside the OpenAPI document itself as an `x-cost-usd` field, so a call is priced by the RESULT you asked for rather than by the bandwidth the transfer happened to consume. That is the distinction to hold on to when comparing against a proxy-metered vendor: the same tweet costs the same whether it arrives in 2 KB or 20 KB. ## Quick answer: which web scraping API or tool should you choose? If you have two minutes rather than twenty, this is the whole page. The choice is not really about price per record, it is about how many sites you need and whether you can wait for an answer. Choose a general web scraping platform when your pipeline touches several different sites, when bot detection and IP rotation are your actual problem, or when a batch job that finishes in an hour is perfectly acceptable. Bright Data is a strong pick in that shape: the proxy network is the product, the dataset catalog is broad, and you pay only for records that come back. Choose a dedicated Twitter and X API when X is the whole job, when something in a user-facing request needs an answer now, or when your product has to act as well as read. A synchronous per-call API returns tweets in the same HTTP response, needs no webhook receiver, and costs $0.0008 a call against $1.50 per 1,000 records pay-as-you-go. Choose the official X API when you sign users in with their own X accounts, when you need a signed data agreement for compliance, or when you need filtered-stream style real-time access. It is the most expensive route per read and the only one that can do those three things. Roll your own only for a one-off research pull. The software is free and the operations are not: accounts, proxies, suspensions, and a silent failure mode where data stops arriving without anything erroring. ## Feature comparison The delivery-model row matters as much as the price, it changes how you integrate. | Dimension | TwitterAPIs | Bright Data | | --- | --- | --- | | Pricing model | Pay per call, $0.0008 per read, ~20 tweets per call | Pay per record, $1.50 per 1,000 pay-as-you-go | | Plan option | None. Top-ups from $10, credits never expire | $499/month includes 384,000 records, then $1.30 per 1,000 | | Response delivery | Synchronous, one HTTP response per call | Asynchronous, trigger a dataset job then poll or receive a webhook | | Failed requests | Failed calls are not billed | Not billed either, per their own pricing page | | Free allowance | $0.50 in credits at signup, no card | 5,000 records a month, no card | | Twitter surface | 109 first-party endpoints, one account | Posts and Profiles datasets, triggered per URL, plus a separate residential proxy network | | Time to first result | The HTTP response itself | Job queue latency, then a webhook callback or a poll | | Infrastructure you build | An HTTP client | A public webhook receiver, or a polling loop with job-state tracking | | Write actions | 44 write endpoints: post, delete, like, retweet, follow, DM, media, lists, Articles | None. It is a data collection platform, not an X client | | Agent and LLM access | Hosted MCP server, 109 tools, same per-call rate | MCP server published, scoped to their scraping and proxy products | | Search by query | Advanced search endpoint, operators and filters, cursor pagination | Discovery by keyword or profile URL on supported datasets, delivered as a job | | Breadth beyond Twitter | Twitter and X only, deliberately | Hundreds of site datasets plus proxy networks, Twitter is one entry | ## What it costs at three volumes Bright Data figures use their pay-as-you-go rate; the $499/month plan is covered below. ### Low volume 10,000 records a month TwitterAPIs $0.40 500 calls x $0.0008, 20 tweets a call. Bright Data $15.00 10,000 records x $1.50 per 1,000, pay-as-you-go. ### Mid volume 100,000 records a month TwitterAPIs $4.00 5,000 calls x $0.0008. Bright Data $150.00 100,000 records x $1.50 per 1,000. Below their plan's 384,000-record floor. ### High volume 1,000,000 records a month TwitterAPIs $40.00 50,000 calls x $0.0008, the same rate as the first call. Bright Data $1,500.00 1,000,000 records x $1.50 per 1,000, pay-as-you-go rate. ## Where Bright Data is genuinely the better tool Bright Data is a proxy and scraping infrastructure company first, and Twitter is one dataset among many. If your pipeline already pulls from a dozen other sites through their residential proxy network, adding Twitter to the same billing relationship and the same job-and-webhook pattern is a real integration saving. Their failed-delivery policy is honest and matches ours: you pay only for what actually comes back. The trade shows up when Twitter is the whole job. Then you are paying platform prices for one target, building and hosting a webhook receiver or a polling loop for data a synchronous API would have handed back in the original response, and their $499/month plan only pays for itself once you are landing 384,000 records or more a month. ## One response vs a triggered job TwitterAPIs ($0.0008/call, synchronous) Bright Data ($1.50/1K records, async) Copy ``` curl -H "Authorization: Bearer YOUR_API_KEY" \ "https://api.twitterapis.com/twitter/tweet/advanced_search?query=web3&limit=20" # $0.0008 for this call. The tweets are in THIS response, # no job to poll and no webhook to build. ``` ``` curl -H "Authorization: Bearer API_TOKEN" \ -H "Content-Type: application/json" \ -d '[{"url":"https://x.com/handle/status/1234567890"}]' \ "https://api.brightdata.com/datasets/v3/trigger?dataset_id=gd_lwxkxvnf1cynvib9co&format=json&uncompressed_webhook=true" # Triggers a job. Results arrive later via webhook, # or you poll the dataset for them. ``` ## What the async model costs you in engineering time The per-record rate is the visible difference. The delivery model is the one that shows up in your sprint. A synchronous API is an HTTP client and nothing else. An asynchronous scraper job is a small distributed system, and it is worth naming the parts before you cost the integration, because none of them are hard and all of them are work. - A public HTTPS endpoint. A webhook receiver has to be reachable from the internet, which means a route, a certificate, and an authentication scheme so that only the vendor can post to it. In local development it also means a tunnel. - Job state you own. A row per triggered job, its snapshot id, when it was fired, whether the callback arrived, and a sweeper for jobs that never came back. That table is the part people forget to budget for. - Idempotency. Callbacks can arrive twice. Without a dedupe key you double-write, and the symptom is a slowly inflating record count rather than an error anyone notices. - Ordering. Results come back in whatever order the jobs finish, so any downstream step that assumed chronological arrival needs a sort and a watermark. - Latency budgeting. If a user is waiting on the result, an async job cannot sit inside that request. You need a pending state in the interface, a poller, and a decision about what the screen shows while nothing has arrived yet. This is genuinely the right design for a nightly backfill of two million records across forty sites. It is the wrong design for a search box. Both of the following fetch the same tweets, and the difference in code is the difference in the architecture. Synchronous, the whole client Async, the parts you still have to build Copy ``` import requests r = requests.get( "https://api.twitterapis.com/twitter/tweet/advanced_search", headers={"Authorization": "Bearer YOUR_API_KEY"}, params={"query": "web3", "cursor": ""}, timeout=30, ) tweets = r.json()["tweets"] # Done. $0.0008 for the call, tweets in hand, # nothing to poll and nothing to receive. ``` ``` # 1. trigger the job job = requests.post(TRIGGER_URL, json=[{"url": profile_url}], headers=AUTH).json() save_pending(job["snapshot_id"]) # you own this table # 2. receive the callback (a route you host, publicly reachable) @app.post("/hooks/scraper") def on_delivery(payload, signature): verify(signature) # you own this too if already_seen(payload["snapshot_id"]): return 200 # idempotency, callbacks repeat store(payload["records"]) mark_complete(payload["snapshot_id"]) # 3. sweep jobs that never called back for job in pending_older_than(minutes=30): poll_or_retry(job) ``` ## Data parsing, and what it costs you A comparison that says Bright Data hands you raw markup to parse is describing the wrong product. Their Web Unlocker returns pages. Their Web Scraper API, which is the product this page compares against, does the parsing for you: their own scraper documentation, read on 5 September 2026, says you send a URL and receive structured JSON or CSV with no proxies, browsers, anti-bot systems or parsing to manage, and their LinkedIn example returns a record with more than 200 fields. On this axis we are the same shape. Both of us return typed data and neither of us asks you to write a selector. So the parsing question is not who does it. It is which fields exist and where the schema is written down. Bright Data's scraper library documents its X and Twitter coverage as profiles and posts. We publish 109 endpoints in one OpenAPI document, 65 of them reads, each with a typed response and an `x-cost-usd` price attached to the endpoint itself. If profiles and posts are the whole job, that breadth buys you nothing and you should weigh the two on price and delivery model instead. If you need follower graphs, list membership, thread expansion, Spaces metadata or direct messages on an account you authenticate as, the deciding question is not parser quality. It is whether the field is offered at all. ## Who owns scraper maintenance With either vendor, not you. That is the honest headline and it is the main reason teams buy a scraping API rather than running Playwright themselves. Bright Data makes the argument explicitly in their own documentation, which carries a Web Scraper API versus DIY page, and it is a fair argument. When X changes its markup, somebody else is on call in both cases. What differs is what each side is maintaining, and it cuts both ways. Bright Data maintains scrapers for thousands of sites, so their team has far more practice at this class of breakage than ours does, and a platform that fixes a hundred targets a month is not slow at it. We maintain one target. That is a narrower surface to watch and a shorter path from a broken field to a shipped fix, but it also means we have no second business line absorbing the cost if X makes a hard change. Neither of us publishes a repair-time commitment on a self-serve plan, and Bright Data reserves its premium SLA for Enterprise, so treat any promise about how fast a break gets fixed as a question to ask in writing rather than a number either page will show you. The practical consequence for your architecture is the same either way. Store what you collect, alert on fields that go empty rather than on HTTP errors, and do not design a feature that assumes a re-fetch will always succeed. A quietly null field is how this failure actually presents, with both vendors. ## Developer experience compared Bright Data has the larger toolbox and it is not close. Their documentation, read on 5 September 2026, ships a Python SDK, a JavaScript SDK, a CLI, an MCP server, a no-code dashboard for running any scraper without integrating, and Scraper Studio for building a custom scraper against a site they do not already cover. They also sell managed services and a datasets marketplace, so there is a path that involves no code at all. We publish an OpenAPI document, 109 MCP tools, and no SDK of our own. If breadth of tooling is what you are shopping for, they win this section outright. The counterweight is what you have to model. Their delivery options are API download, webhooks, cloud storage to S3, Google Cloud Storage, Azure or Snowflake, and streaming, which is genuinely more capable than anything we offer and is exactly the right shape for a nightly job that lands a million records in a warehouse. It is more than you need to wire up if the answer you want is twenty tweets in the response to the request you just sent. Bright Data does offer a synchronous mode, so this is a difference of default rather than of possibility. Ours is one request and one response, priced per call, with no job to poll and no receiver to host. Pick the tool whose default matches the shape of your job, because the default is what you will actually build against. ## Why teams switch from Bright Data We only see the ones who leave, which is a biased sample and worth saying up front. Teams happy with Bright Data do not write to us. With that caveat, the reasons people give when they move a Twitter workload off a general scraping platform fall into four recognisable shapes, and none of them are about the platform being bad at what it does. - The catalog stopped being the reason. A pipeline starts across six sites and consolidates onto one. Once X is the only remaining source, you are paying platform pricing for a catalog you no longer use, and the proxy infrastructure that justified the rate is solving a problem the dedicated API already solved on its side. - A user-facing feature arrived. Batch collection is fine until someone ships a search box, a live profile lookup or an in-app feed. Async delivery cannot sit inside a request a human is waiting on, and retrofitting a synchronous path around a job-and-webhook API means running a second data source anyway. - The per-record rate compounded. $1.50 per 1,000 records is unremarkable at 10,000 records a month, which is $15. At a million records it is $1,500 against roughly $40 on a per-call rate. Nothing changed except the volume, and the model that was cheap to start became the largest line in the data budget. - The product needed to write, not just read. Scraping platforms collect. They do not post a tweet, send a direct message, follow an account or manage a list. The moment a roadmap item requires acting on X rather than reading it, a collection platform is structurally the wrong layer and a second integration appears. The mirror image is also true and we would rather state it than leave it implied. Teams leave us for a general platform when they add a second and third site. If your roadmap has Instagram and LinkedIn on it, a Twitter-only API is the wrong shape and we will say so. ## Decision tree: which Bright Data alternative to pick Work down these in order. The first one that matches is your answer, and it is deliberately not always us. 1. Do users sign in with their own X accounts so your product can act for them? Then you need the official X API. The consent-bound OAuth flow is X's and cannot be replicated by any third party, whatever else you pair it with. Third party APIs handle the public read side around it. 2. Do you need three or more platforms, not just X? Stay on a general platform, whether that is Bright Data or a multi-network unified API. One billing relationship and one integration pattern across sites is worth more than a better rate on one of them. 3. Is anything user-facing waiting on the result? Then you need a synchronous API. Async delivery means a pending state, a poller and a callback receiver, which is a lot of machinery to put behind a search box. 4. Does your product need to post, reply, DM or manage lists? Then you need an API with write endpoints. Collection platforms do not have them, and adding a second vendor for the write half is the expensive outcome. 5. Is your volume spiky, seasonal or exploratory? Then avoid anything with a monthly floor. A $499 plan at 40,000 records is $12.48 per 1,000, nine times the plan's own headline overage rate, because you are buying 384,000 records to use a tenth of them. 6. None of the above, and you just want tweets cheaply? A per-call Twitter API is usually the cheapest route, and the exception is worth knowing: on a polling job over a small watch list we come fourth of five in our own priced comparison, because a per-call meter charges for every empty check while a per-post meter does not. On anything that collects a lot of distinct posts we win by a wide margin. That is the case we are making here, and it only applies once the five questions above have all come back no. ## How long a backfill takes, and why the answer differs Cost per record is the question everyone asks and wall-clock time is the one that decides whether a project is viable. The two delivery models fail in opposite directions here, and it is worth knowing which failure you are buying. A batch platform is fast in aggregate and slow per item. You hand over a list of URLs, the platform fans it out across a proxy network with high parallelism, and a large job completes in one pass. Any single record, though, is only available once the job that contained it finished. There is no way to ask for one profile and get it back in 200 milliseconds, because the unit of work is the job, not the request. A synchronous API is fast per item and paced in aggregate. One call, one response, and your throughput is a function of how many concurrent requests you run. A million tweets at 20 per call is 50,000 calls. At 10 concurrent requests taking roughly a second each, that is under two hours of wall clock, and the parallelism is a number in your own worker pool rather than a queue you do not control. The practical consequence is architectural rather than numeric. If your product shows a user something derived from X data while they wait, the async model cannot serve that path and you will end up running a second source for it. If your product runs a nightly job over a fixed URL list and nobody is watching a spinner, the batch model is well suited and the parallelism is somebody else's problem. One detail worth checking on either vendor before sizing a historical pull: the concurrency ceiling. A rate that looks cheap stops being cheap if the job takes eleven days, and neither a per-record price nor a per-call price tells you that on its own. ## What neither of these can return Comparison pages are usually a list of what each side has. This is the list of what neither side has, and it saves more time than the feature table does, because a limit you discover in week three of an integration is far more expensive than a rate you priced wrong. - Protected accounts. If a profile is private, its posts are not publicly visible and no third party can return them. Any vendor implying otherwise is describing something you should not buy. - Deleted content. Once a post is gone from X it is gone from the source both of us read. Retention is your responsibility, which in practice means storing what you collect rather than planning to re-fetch it later. - Other people's direct messages. Our direct message endpoints operate on an account you control and authenticate as. They are not a window into anybody else's inbox, and no data platform offers one. - Ad spend and paid performance. Campaign objects, spend and paid impressions live behind the X Ads API and an advertiser relationship. Neither a scraping platform nor a data API replaces that. - Guaranteed completeness of the full archive. Both of us serve what is publicly reachable. If your requirement is a contractually complete historical corpus with a signed agreement behind it, that is an enterprise relationship with X and not a line item on anybody's pricing page. None of this is a criticism of either product. It is the boundary of the category, and knowing it before you scope a feature is worth more than a percentage point on a rate card. ## The verdict Bright Data and TwitterAPIs are not really the same category, and the comparison is only fair on the one job they overlap on: getting X data into your database. On that job, per call at $0.0008 beats per record at $1.50 per 1,000 by roughly 14x to 37x depending on how full your pages come back, and synchronous delivery removes a webhook receiver, a job table and an idempotency key from your codebase. On every other job Bright Data is the stronger tool and we are not competitive at all. Hundreds of site datasets, a residential proxy network that is the actual product, bot-detection handling across targets we have never touched, and a delivery model built for volume rather than for latency. If X is one source in a wide pipeline, their platform is doing something we deliberately do not do. So the verdict is a question rather than a winner. If you removed X from your pipeline tomorrow, would you still be paying Bright Data? If yes, keep them and let X ride along on the same account. If no, you are paying platform infrastructure prices for a single target, and a dedicated API is both cheaper and less code. ## Other comparisons worth reading Each vendor loses on a different axis, so the one that matters depends on how you buy. These three cover the rest of the field. - [TwitterAPIs vs SocialData](https://www.twitterapis.com/twitterapis-vs-socialdata) , per-item pricing against a per-call rate. - [TwitterAPIs vs Apify](https://www.twitterapis.com/twitterapis-vs-apify) , compute units and expiring credits. - [TwitterAPIs vs Scrapingdog](https://www.twitterapis.com/twitterapis-vs-scrapingdog) , the 5x Twitter credit multiplier. - [The full Twitter API alternatives roundup](https://www.twitterapis.com/twitter-api-alternatives) , every vendor we have priced, in one table. ### Start with $0.50 in free credits One synchronous call, up to 20 tweets back in the same response, no webhook to build and no plan to size against. [Start free, $0.50 in credits](https://www.twitterapis.com/signup)[Open cost calculator](https://www.twitterapis.com/twitter-api-cost-calculator) ## Check out similar blogs For more detail than a head-to-head page can carry, two of our posts go deeper on exactly this category: - [Best Twitter Scraper 2026: API, Browser, Python Tools](https://www.twitterapis.com/blogs/best-twitter-api-for-scraping) , a full comparison across the official API, third-party APIs, browser-based scrapers, and Python libraries, not just the one pair this page covers. - [Cheapest Twitter API 2026: 8 Providers Ranked by Real Per-1,000-Tweet Cost](https://www.twitterapis.com/blogs/cheapest-twitter-api-2026-8-providers-ranked-by-real-per-1000-tweet-cost) , where every vendor mentioned on this page lands once billing traps are priced in, not just the headline rate. ## Frequently asked questions ### Is a Bright Data record the same as a TwitterAPIs call? No. Bright Data bills per record their scraper delivers, one tweet or one profile, so their $1.50 per 1,000 is an exact rate. TwitterAPIs bills per call, and a single search or timeline call returns up to 20 tweet objects, so our $0.04 per 1,000 is a modelled figure assuming a full 20-tweet page. Comparing the two directly overstates the gap. Measured across 396,817 of our own read calls, pages averaged about 13 tweets and search pages closer to 8, putting our real delivered cost nearer $0.06 to $0.11 per 1,000. Bright Data still runs far above that, roughly 14x to 37x on the pay-as-you-go rate depending on how full your pages come back, but 37x is the best case and not the typical one. ### Does Bright Data have a subscription plan? Yes, alongside pay-as-you-go. Their $499/month plan includes 384,000 records, with overage billed at $1.30 per 1,000 beyond that. At exactly that volume the plan works out cheaper than the pay-as-you-go rate; below it, you are paying for records you never touch. TwitterAPIs has no plan to size against, you buy credits and they never expire. ### Is there a promo code for Bright Data? Bright Data advertises a 25% discount with the code APIS25, though their own page states the discount lasts 3 months in one place and 6 months in another. We are not resolving that inconsistency for them, check the live page for the current term before you rely on it. ### Can I try TwitterAPIs without paying anything first? Yes. New accounts get $0.50 in free credits at signup with no card required, roughly 625 calls or about 12,500 tweets at the standard rate, and top-ups start at $10 with no subscription and no expiry. ### What does the $499 plan actually work out at per 1,000 records? It depends entirely on how much of it you use, which is the point. Fully consumed, $499 for 384,000 records is about $1.30 per 1,000, matching their stated overage rate and undercutting the $1.50 pay-as-you-go price. At 40,000 records, a tenth of the allowance, the same $499 is $12.48 per 1,000, roughly nine times the plan's own headline rate. Our $0.0008 per call does not move: it is the same number on the first call of the month and the last, because there is no allowance to fill. ### Can an AI agent call either of these directly? Both publish an MCP server, so the answer is yes in both cases, but they expose different things. Bright Data's covers their scraping and proxy products across the site catalog. Ours exposes 109 tools mapped onto the same Twitter and X endpoints described on this page, at the same $0.0008 per call, so a model can search, read a timeline, pull a follower list or post without anyone writing tool definitions first. ### Why does Bright Data need a webhook? Their Twitter Scraper API is asynchronous. You POST the URLs you want scraped to a trigger endpoint, and results come back later through a webhook callback or a dataset you poll, not in the response to your original request. TwitterAPIs is synchronous: one call, one response, with the data in that same reply. If your product needs an answer inside a user-facing request, the async model adds real latency and a callback endpoint to build and maintain. ### Does Bright Data charge for failed scrapes? No. Their pricing page states plainly: pay only for what is successfully delivered, no charges for failed deliveries. We hold the same policy, failed calls are not billed on TwitterAPIs either. ### When is Bright Data the better choice? When Twitter is one source among several and you already run other scraping workloads through Bright Data's residential proxy network. Their infrastructure handles bot detection and IP rotation across a large catalog of sites, and consolidating billing and tooling under one vendor is worth real engineering time if your pipeline touches more than one platform. If Twitter and X are the whole job, a synchronous, purpose-built API is both cheaper and simpler to integrate. ### Does Bright Data support posting to X, or is it read-only? Bright Data is a data collection platform, so it reads. It does not post a tweet, reply, send a direct message, follow an account, upload media or manage a list, because that is not what a scraping and proxy product is for. TwitterAPIs publishes 44 write endpoints alongside 65 reads on the same key and the same billing, so a product that starts by reading and later needs to act does not need a second vendor. If your roadmap is read-only forever, this difference costs you nothing. ### Which one is better for a historical backfill? Neither answer is universal. For a one-off pull across a fixed list of URLs spanning several sites, a batch platform is well suited: you submit the list, it fans out across the proxy network, and you collect the results when the job finishes. For a Twitter-only backfill, a per-call API is cheaper by an order of magnitude and the parallelism is a number in your own worker pool rather than a queue you cannot see into. The question that decides it is whether the backfill touches sites other than X. ### Is per record or per call the fairer way to compare? Per delivered item, which is neither vendor's native unit and is why this page shows both. Bright Data bills exactly per record, so their number needs no adjustment. We bill per call, and a call returns up to 20 tweets, so our headline assumes a full page. Measured across 396,817 of our own read calls, pages averaged about 13 tweets and search pages closer to 8, which puts our real delivered cost at roughly $0.06 to $0.11 per 1,000 rather than the $0.04 a full page implies. Use those numbers rather than the headline when you build your own model. [Start Free](https://www.twitterapis.com/signup) ## Next read Continue exploring related pages: [ TwitterAPIs vs SocialData SocialData bills $0.0002 per tweet or profile returned vs TwitterAPIs at $0.0008 per call, about 20 tweets a call. ](https://www.twitterapis.com/twitterapis-vs-socialdata)[ TwitterAPIs vs Apify Twitter scraper Apify bills monthly compute units (1 CU = 1 GB RAM/hour) with credits that expire; TwitterAPIs is $0.0008 per call, no plan, credits never expire. ](https://www.twitterapis.com/twitterapis-vs-apify)[ Twitter API v2 pricing vs TwitterAPIs Side-by-side endpoints, pricing, auth, and response shape, same data, 100x cheaper. ](https://www.twitterapis.com/twitter-api-pricing)[ Twitter API alternatives and X API alternatives Evaluate alternatives by cost model, limits, and integration fit. ](https://www.twitterapis.com/twitter-api-alternatives) [ TwitterAPIs ](https://www.twitterapis.com/) The cheapest pay-as-you-go Twitter and X API. $0.0008 per call, which works out to $0.04 per 1,000 tweets on a full 20-tweet page. 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