Heroku Postgres is now based on AWS Aurora

Heroku Postgres Essential tiers & pricing

• New “Essential” plans: 1/10/32 GB storage, low connection limits (20–40), $5–$20/month.
• Positioned as entry-level, multi-tenant Aurora-backed DBs for toy apps/MVPs and pre-prod.
• Replace old row-limited mini/basic tiers at same prices but with storage-based limits.
• No replication, modest uptime target (99.5%), and other “full” features omitted; clearly distinct from larger dedicated plans.
• Larger Aurora-backed dedicated offerings are promised “relatively soon.”

Heroku pricing vs direct cloud costs

• Several commenters say traditional Heroku Postgres has very high margins; some report 5–10x savings by moving to AWS or self-managed Postgres.
• Others note current top-end Heroku plans are still dramatically more expensive than equivalent AWS instances.
• At the very low end ($5 plans), some are unsure how much margin actually remains.

Aurora cost, performance, and design

• Some report Aurora as reliable and performant (especially with large row counts and upserts), but often the dominant line item in their AWS bill.
• Aurora’s IO-based billing can be painful; IO-optimized storage is mentioned as a newer, more predictable option.
• Others argue RDS or self-hosted Postgres on NVMe can be cheaper and faster, while Aurora’s value is in autoscaling storage, multi-AZ, and cross-region features.
• Aurora’s log-structured storage and separation of compute and storage are cited as genuine technical innovations.

Aurora gotchas and operational issues

• Reports of expensive I/O for poorly tuned queries; big cost drops after switching to self-managed Postgres.
• Complaints about opaque behavior and undocumented differences vs vanilla Postgres/MySQL (e.g., temp storage limits, non-atomic table rename semantics, global write-forwarding latency).
• Serverless v1 could scale to zero; v2 no longer does. Typical customers reportedly don’t use Serverless.
• Advice to use pgbouncer rather than AWS’s own proxy in some setups.

Managed vs self-hosted Postgres

• One camp: running your own Postgres is straightforward and avoids Aurora/Heroku markups.
• Counterpoint: production-grade clusters (HA, backups, PITR, monitoring, upgrades) are non-trivial, not core to most businesses, and require expensive specialists.
• Broader debate about over-outsourcing infra vs under-investing in DB skills; consensus that DB fundamentals still matter even if using managed services.

Who still uses Heroku & alternatives

• Many still use Heroku for simplicity: “git push” deploys, low-ops, easier compliance (e.g., SOC 2) for small SaaS.
• Others feel it’s stagnated (slow on HTTP/2, gRPC, IPv6; expensive VPC peering; async HA replication that can lose data).
• Some are actively migrating databases to specialized Postgres providers (e.g., Crunchy) citing better performance, features like logical replication, and more granular storage pricing.
• For app hosting, alternatives mentioned include Render, Railway, Northflank, Fly.io, DigitalOcean App Platform, ECS, etc., but several people find their developer experience still inferior or buggy compared to Heroku.
• Negative sentiment from users in India over Heroku’s handling of card-regulation changes, perceived as abandoning smaller customers.

Cloud ecosystem & credits

• Mixed views on startup behavior: some say free credits from major clouds keep startups on AWS/GCP/Azure; others highlight growth of higher-level platforms (Vercel, Netlify, Supabase, Render, Railway).
• One startup describes heavy use of GPU credits across clouds, planning to move to owned hardware once credits expire.

AWS developer experience (Amplify)

• A long critique calls Amplify one of AWS’s worst services: confusing split between CLI and GUI workflows, scattered CloudFormation/IAM/Cognito resources, inconsistent UIs, and documentation gaps around configuration files.
• The experience is contrasted unfavorably with simpler static hosting/CI solutions like Netlify or Cloudflare Pages.