TL;DR: Tested 4 approaches to access Twitter data after APIv2 became unusable. Winner: twitterapi.io (100K free credits). DIY scraping costs $10+/GB in proxies. Code included for Next.js + Drizzle ORM. See my app that got me blocked by YC's CEO.
The Backstory: When Twitter Pulled the Rug
Two weeks ago, my rant about Twitter's API collapse blew up with 245K views.Got flooded in the comments with alternatives! Thank you! I spent 60+ hours stress-testing every solution under real-world conditions.
Here's what actually works in mid-2025.
⚔️ The Contenders: 4 Paths Through the Wasteland
1. Self-Hosted: Nitter (The Idealist's Trap)
nitter
The Promise: Open-source, privacy-focused Twitter frontend with RSS feeds.
The Reality:
# Setup pain points
$ git clone https://github.com/zedeus/nitter
$ docker-compose up -d # Surprise! Needs guest account pool + proxies
✅ Pros:
- Full control over data pipeline
- No third-party rate limits
❌ Cons:
- Constant guest account rotation
- Public instances get nuked within hours
- ≈40% failure rate during my load tests
Verdict: ❤️ for hobbyists, ☠️ for production.
2. Managed APIs (The Pragmatic Choice)
🥇 twitterapi.io - My Winner
Pricing That Doesn't Suck:
- 100,000 free credits on signup (≈6,600 tweets)
- $0.15 per 1k tweets (15 credits/tweet)
- Purchased credits never expire
Performance:
▶ ab -n 1000 -c 50 https://api.twitterapi.io/v1/user_tweets
Requests per second: 142.51 [#/sec] (mean)
✅ Why it wins:
- OpenAPI spec = instant openapi-typescript integration
- Crypto payments accepted
- Webhook support for real-time monitoring
❌ Gotcha: No recurring free tier after signup bonus.
🥈 Apify - The Data Scientist's Hammer
API Twitter Scraper
Pricing:
- $5 free monthly credits
- ≈$0.45 per 1k tweets
✅ Killer features:
- Scrape followers/likes/search with point-and-click config
- Export to S3/BigQuery
- Handle 1M+ tweet jobs
❌ Warning: Costs balloon if your scraper isn't optimized.
3. DIY Scraping (The Pain Cave)
Toolchain:
the-convocation/twitter-scraper
- Playwright
- IPRoyal residential proxies ($15/GB)
The Cold Hard Truth:
You'll hate your life
✅ Pros:
- Ultimate flexibility
❌ Cons:
- 15+ hrs/week maintaining scrapers
- $10-$50/day in proxy costs
- Your personal Twitter account will get banned
☠️ Critical Lessons (Paid in Blood)
- My app (@TheRoastBotApp) got limited for "inauthentic behavior" after 48 hrs
- Residential proxies ≠ invisibility cloaks - Twitter fingerprints browser/network stacks
- Always abstract your data layer:
// Generic interface saved me
interface SocialDataSource {
getUserTweets(userId: string): PromiseTweet[]>;
}
class TwitterAPI implements SocialDataSource { ... }
class ApifySource implements SocialDataSource { ... } // Easy swap!
💻 Technical Deep Dive: Next.js + Drizzle ORM
Full Architecture:
graph LR
A[Next.js App Router] --> B[twitterapi.io]
A --> C[PostgreSQL]
C --> D[Drizzle ORM]
D --> E[The Roast Bot Frontend]
Implementation:
lib/twitter.ts
import { drizzle } from 'drizzle-orm/postgres-js';
import postgres from 'postgres';
const connection = postgres(process.env.DATABASE_URL!);
export const db = drizzle(connection);
export const getTweets = async (userId: string) => {
const res = await fetch(
`https://api.twitterapi.io/v1/user_tweets?user_id=${userId}`,
{ headers: {'x-api-key': `${process.env.TWITTERAPI_KEY}` } }
);
return res.json();
};
drizzle/schema.ts
import { pgTable, text, timestamp } from 'drizzle-orm/pg-core';
export const tweets = pgTable('tweets', {
id: text('id').primaryKey(),
userId: text('user_id').notNull(),
content: text('content').notNull(),
scrapedAt: timestamp('scraped_at').defaultNow(),
});
app/api/ingest/route.ts
import { db } from '@/lib/db';
import { tweets } from '@/drizzle/schema';
export async function POST(req: Request) {
const { userId } = await req.json();
const tweetData = await getTweets(userId);
await db.insert(tweets).values(tweetData).onConflictDoNo thing();
return new Response(JSON.stringify({ success: true }), {
status: 200,
headers: { 'Content-Type': 'application/json' }
});
}
🏆 The Verdict
| twitterapi.io | $0.15 | Minutes | ★★★★☆ | Production apps |
| Apify | ~$0.45 | Hours | ★★★★☆ | Data mining |
| Nitter | Server costs | Days | ★★☆☆☆ | Hobby projects |
| DIY + Proxies | Variable (High) | Weeks | ★☆☆☆☆ | Total control |
Epilogue: The Roast Bot Rebellion
This research birthed The Roast Bot - which got me blocked by YC's CEO in 48 hours. Worth it.
Final Advice:
"Treat Twitter data like radioactive material—minimize exposure, and always have a containment plan."
Discussion Time:
- What's your scraping horror story?
- Any better solutions I missed?
- Want the Bun worker code? Ask below! 👇
Like this guide? I write frequently about Next.js and scraping at @TheRoastBotApp (until Elon bans me).
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