Neon's Autoscaling Bill Eating Your Budget? Here Are Real Alternatives

So you got hit with that surprise bill and now you're here researching alternatives. You're not alone - I've been tracking migration stories since Neon launched, and three things consistently drive teams away from it. None of this is from some bullshit "analysis" - it's from actual conversations with developers who got burned.

Spoiler alert: if you're here, you've probably already decided to leave. You're just looking for validation that you're not crazy for wanting predictable database bills.

The Autoscaling Bill Shock

Neon's autoscaling will screw you over when you least expect it. I watched a friend's side project get featured on Hacker News - his bill went from like fifteen bucks to... I don't know, maybe 350? Could have been 420? Either way, fucking brutal because traffic spiked and compute scaled to max.

The official pricing looks reasonable until you dig into it. Recent pricing changes bumped Launch tier to $0.14/CU-hour with a $5 monthly minimum, Scale tier is $0.26/CU-hour. When your app needs consistent compute, those hours add up fast. A 2 CU instance running 24/7 costs probably like 180-250 bucks a month on Launch tier - before storage.

Here's the thing nobody tells you: Neon's database branches are brilliant for development but each branch storing changes costs $0.35/GB-month. Create a few feature branches with decent data and you're looking at surprise storage bills.

What actually happens with costs:

• Dev branches pile up storage costs ($0.35/GB-month each)
• Autoscaling hits during traffic spikes with no warning
• Point-in-time recovery adds $0.20/GB-month for data changes
• Connection pooling limits force compute upgrades

What we all learned the hard way: Neon saves money for truly idle apps but costs way more for anything with steady traffic - like 2x, maybe 3x? The compute-hour pricing model works against you for steady workloads.

You Don't Actually Own Your Database

Want superuser access? Too bad. Need a specific PostgreSQL extension that isn't on Neon's approved list? Sorry, can't help you. This managed service approach works great until it doesn't. Other managed PostgreSQL services like Railway or self-hosted solutions give you full control.

I've seen teams hit these walls:

• Custom extensions blocked - can't install what you need
• Configuration limits - can't tune for your specific workload
• Single region deployment - can't get closer to global users
• PgBouncer constraints - connection pooling doesn't fit all patterns

I've seen this story play out over and over: start simple, grow complex, hit limitations, migrate away.

Cold Starts Will Ruin Your Day

Neon's 300-500ms cold starts seem fine on paper. In reality, they'll destroy user experience for anything real-time. I've built APIs where that half-second delay killed the entire feature.

Cold starts break these use cases:

• Real-time chat applications (users see "connecting..." for 500ms)
• Financial APIs with SLA requirements (you get ECONNREFUSED during cold starts)
• Gaming backends where latency matters (players notice the pause)
• Any API called from mobile apps (users notice the delay and think it's broken)

How Migrations Actually Happen

Forget the three-phase corporate bullshit. Here's how teams really migrate:

1. Panic: Usually triggered by a surprise bill or performance issue
2. Research: Frantically google alternatives while your app is slow/expensive
3. Test: Spin up a PostgreSQL instance somewhere and test your schema
4. Migrate: pg_dump during low traffic and pray nothing breaks

Most successful migrations I've seen follow PostgreSQL compatibility. Teams picking MySQL (PlanetScale) or SQLite (Turso) spend weeks rewriting queries and dealing with weird edge cases. PlanetScale's own PostgreSQL migration guide shows how complex this conversion really is - they wouldn't need a detailed guide if it was simple.

The brutal truth: teams don't migrate because Neon is bad - they migrate because they outgrew what serverless PostgreSQL can handle, or got tired of unpredictable bills.

Cool, you picked an alternative from the table above. Now comes the fun part - actually moving your data without breaking everything. Forget the success rate bullshit in migration guides. Here's what really happens when you migrate away from Neon, based on actual war stories from developers who've done it.

The PostgreSQL "Easy" Migration (Spoiler: It's Not Always Easy)

What they tell you: "Just pg_dump and pg_restore, it's PostgreSQL!"

What actually happens: Yeah, it's PostgreSQL, but you'll hit weird edge cases you didn't expect.

Real example: Migrated like a 15GB SaaS database to Supabase last year. Thought it'd be easy since it's "just PostgreSQL"...

Migration took way longer than expected. Connection pooling was completely fucked up - kept getting server closed the connection unexpectedly and FATAL: remaining connection slots are reserved for non-replication superuser connections. Spent 4 hours debugging before I realized Supabase uses session pooling while Neon uses transaction mode. Had to rewrite like 8 connection handling functions.

Then some extension I was using (pg_similarity) wasn't available on Supabase, broke my search functionality completely. Plus I had test data mixed with prod schema because of all those Neon branches I'd forgotten about - took me 6 hours to clean up 3 months of "quick test" branches that were still accumulating storage costs.

Total time: Took maybe a week and a half instead of the "1 day" I thought it would take. Minimal downtime though - like 20 minutes while DNS switched, so that was good.

The gotchas nobody mentions:

• Connection pooling works differently - Supabase uses session mode, Neon uses transaction mode (PgBouncer settings vary)
• Some PostgreSQL extensions aren't available - pg_similarity works on Neon but not Supabase (extension compatibility guide)
• Neon's branching creates schema complexity you forgot about - test data gets mixed with prod schemas
• SSL mode changes from require to prefer break some ORMs (migration checklist)

Teams that succeed: Have spare time to debug weird issues. Teams that fail: Need it done yesterday and hit the first blocker.

The "Cost Savings" Migration (Where You Become the DBA)

What they tell you: "Self-hosted PostgreSQL will save money!"

What actually happens: You save money but lose your weekends.

Real story: Friend migrated his ~$150/month Neon app to like a $25 Hetzner VPS. Here's what he didn't budget for:

• First week: Took him like 3 days just to get PostgreSQL installed and not completely fucked up
• Month 2: Database crashed at 2am with "no space left on device" - spent 4 hours figuring out log rotation wasn't working, plus lost like 6 hours of data
• Month 4: Got hacked because he forgot to update PostgreSQL security patches - CVE-2023-39417 vulnerability in PostgreSQL 15.3, allowed SQL injection through extension functions. Spent the weekend rebuilding the entire server from scratch and restoring from a 3-day-old backup because recent backups were corrupted
• Month 6: Had to upgrade RAM because shared_buffers was misconfigured and queries were timing out. Took him a weekend to figure out why.

Total cost: $25/month + probably 4-5 hours/month fixing random shit + one weekend of downtime recovery that absolutely sucked.

Railway alternative: Same friend later moved to Railway. $20/month, zero maintenance. "I should have done this first," he told me.

The reality check:

• Self-hosting saves money if you value your time at $0/hour
• Railway costs 2x more but eliminates all the bullshit
• AWS RDS is 3x more but handles everything including your 3am emergencies

The "Different Database Engine" Migration (Why Did I Do This To Myself?)

What they tell you: "PlanetScale has amazing features!"

What actually happens: You spend 3 weeks rewriting queries for MySQL.

Actual migration pain points:

• PostgreSQL RETURNING clause doesn't exist in MySQL - had to rewrite 47 queries (PlanetScale migration guide confirms this pain)
• UUID primary keys became BINARY(16) - broke half the admin interface
• Array columns needed to become JSON - migration scripts were hell
• Different JSON operators meant updating every search query (PostgreSQL to MySQL differences)

One team's timeline:

• Week 1: "This will be easy, just change the ORM config" (spoiler: it wasn't)
• Week 2: "Why doesn't this query work? Oh, MySQL..." (discovered 20+ broken queries)
• Week 3: "Fuck it, we're going back to PostgreSQL" (after rewriting like half their codebase)

They ended up on Railway. Something like $15-20/month, PostgreSQL, zero query rewrites. Should've done that from the start.

The masochist special: SQLite (Turso) is even worse. You're not just changing database engines, you're changing how your entire app works. Only do this if you absolutely need edge computing.

The Actual Migration Success Framework

If you just want to escape Neon's billing surprises:

1. Railway - PostgreSQL, predictable pricing, done in 2 days
2. Supabase - PostgreSQL + auth features, done in 3-4 days

If you're spending $200+ per month on Neon:

1. AWS Aurora - Enterprise PostgreSQL, worth the setup pain
2. Self-hosted - If you enjoy database administration

If you hate money and love complexity:

1. PlanetScale - Rewrite everything for MySQL features you might not need
2. Turso - Convince yourself that SQLite at scale makes sense.

What Nobody Admits About Migrations

"Zero downtime" migrations: Bullshit unless you set up logical replication, which takes planning. AWS DMS documentation shows how complex this really gets.

Migration time estimates: Double whatever you think it'll take. Triple if you're changing database engines. I learned this the hard way.

Rollback plans: Test them before you need them. I've seen teams stuck in limbo because rollback didn't work.

The real success metric: How fast you can get back to building features instead of fighting database infrastructure.

Most successful migrations I've seen follow the same pattern: pick PostgreSQL-compatible alternative (PostgreSQL hosting comparison), do migration during low traffic, fix the edge cases that pop up, move on with life. Migration best practices consistently recommend this approach.

The failures all try to optimize too many things at once: new database, new pricing model, new features, new query language. Pick one change, nail it, then optimize later.