Aurora vs RDS PostgreSQL vs EC2: Costs, Performance & Multi-Region Compared (2025)
A brutally honest comparison of running PostgreSQL on Aurora, RDS, and EC2. We cover costs, performance, failover, global replicas, and all the tradeoffs AWS won't tell you in their marketing docs.
Aurora vs RDS PostgreSQL vs EC2: Costs, Performance & Multi-Region Compared (2025)
⚠️ Important Disclaimer: AWS pricing, features, and capabilities change frequently. This comparison is accurate as of December 2025, but may become outdated. Always verify current pricing and features in the AWS documentation before making architectural decisions.
The Question That Keeps DBAs Up at Night
You need PostgreSQL in AWS. You have three choices:
- Amazon Aurora PostgreSQL - AWS's fancy, cloud-native rewrite
- Amazon RDS PostgreSQL - Managed PostgreSQL, the boring (reliable) choice
- PostgreSQL on EC2 - DIY mode activated
Each has passionate advocates and equally passionate critics. Let's cut through the marketing and look at the reality.
Architecture Comparison
High-Level Architecture Differences
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The Cost Reality: Let's Talk Numbers
Monthly Cost Comparison (us-east-1, December 2025)
Scenario: 100GB database, moderate workload (db.r6g.xlarge / r6g.xlarge)
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| Component | Aurora | RDS PostgreSQL | EC2 Self-Managed |
|---|---|---|---|
| Compute (db.r6g.xlarge/r6g.xlarge) | ~$584/mo | ~$336/mo | ~$122/mo |
| Storage (100GB) | $0.10/GB + I/O | $0.115/GB (gp3) | $0.08/GB (gp3) |
| Backup Storage (100GB) | Free (< DB size) | Free (< DB size) | S3 costs (~$2.30) |
| I/O Costs | $0.20 per 1M I/O | Included | Included |
| Read Replicas (1 replica) | +$584/mo | +$336/mo | +$122/mo |
| Multi-AZ | Included in base | +100% compute | DIY |
| Ops/Management | $0 | $0 | Your salary ÷ 12 |
Estimated Monthly Total:
- Aurora: $800-1,200+ (highly variable based on I/O)
- RDS: $450-650 (predictable)
- EC2: $200-400 (+ hidden ops costs)
The Cost Catch: Aurora's I/O pricing can surprise you. A write-heavy workload can add $200-500/month in I/O costs alone.
Performance: Benchmarks and Reality
Write Performance
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Aurora Advantages:
- Writes are fast due to offloaded storage I/O
- Up to 15 low-latency read replicas
- Storage scales automatically (up to 128TB)
RDS Advantages:
- Predictable, standard PostgreSQL performance
- You know exactly what you're getting
- No surprise I/O costs
EC2 Advantages:
- You can tune kernel parameters, storage, and everything
- Can use NVMe instance store for temporary massive IOPS
- Full control over PostgreSQL configuration
Reality Check: For 90% of workloads, the performance difference is negligible. Your application architecture matters more than Aurora vs RDS.
High Availability & Failover
Failover Process Comparison
| Step | Aurora | RDS Multi-AZ | EC2 (Your Setup) |
|---|---|---|---|
| Detection | Automatic | Automatic | Manual or scripted |
| Promotion | 30-60 seconds | 60-120 seconds | 2-30 minutes |
| DNS Update | Automatic (Route53) | Automatic (Route53) | Manual or scripted |
| Total Downtime | 30-60 seconds | 60-120 seconds | 5-30+ minutes |
| Data Loss Risk | None (6 copies) | None (sync replication) | Depends on setup |
Availability SLA Comparison
| Feature | Aurora | RDS Multi-AZ | EC2 (Your Setup) |
|---|---|---|---|
| SLA | 99.99% (Multi-AZ) | 99.95% (Multi-AZ) | Whatever you build |
| Automatic Failover | Yes (30-60s) | Yes (60-120s) | If you build it |
| Data Replication | 6 copies, 3 AZs | Synchronous to standby | pglogical/streaming |
| Read Replica Lag | < 20ms typical | Varies (50ms-5s) | Depends on setup |
| Point-in-Time Recovery | 1 second granularity | 5 minute granularity | Depends on setup |
| Zero-Downtime Patching | Yes (for replicas) | No | You wish |
Aurora Wins:
- Fastest failover
- Most resilient storage (6 copies)
- Best read replica lag
RDS Wins:
- Good enough HA for most use cases
- Simpler to reason about
- No surprise behaviors
EC2 Wins:
- Nothing here (for HA)
- You're on your own
- But hey, you learned something
Multi-Region and Global Deployment
Global Deployment Overview
Aurora Global Database:
- Primary region replicates to up to 5 secondary regions
- < 1 second replication lag typical
- Promote secondary to primary in < 1 minute
- Dedicated cross-region infrastructure
RDS Cross-Region:
- Primary with async read replicas in other regions
- Seconds to minutes replication lag
- Manual promotion (5-15 minutes)
- Uses standard read replica mechanism
EC2 Multi-Region:
- DIY replication (pglogical/streaming)
- Replication lag depends on your setup
- Your custom scripts for failover (10+ minutes)
- Full control, full responsibility
Multi-Region Feature Comparison
| Feature | Aurora Global | RDS Cross-Region | EC2 Multi-Region |
|---|---|---|---|
| Replication Lag | < 1 second | Seconds to minutes | Depends on setup |
| Dedicated Replication Infra | Yes (AWS-managed) | Uses read replicas | You build it |
| Secondary Regions (max) | 5 | Unlimited (replicas) | Unlimited (DIY) |
| Failover Time | < 1 minute (RTO) | 5-15 minutes | 10+ minutes |
| Recovery Point | < 1 second (RPO) | Varies | Varies |
| Cost | $$$ (highest) | $$ (moderate) | $ (compute only) |
| Write to Secondary | No (read-only) | No (read-only) | Can setup multi-master |
| Application Changes | Minimal | Minimal | Depends on setup |
Aurora Global Database:
- Best for: True global applications, financial systems, gaming
- RPO: < 1 second
- RTO: < 1 minute
- Cost: ~2x primary region cost per secondary region
- Catch: Still single-master, read-only secondaries
RDS Cross-Region Read Replicas:
- Best for: DR strategy, regional read scaling
- RPO: Seconds to minutes
- RTO: 5-15 minutes (manual promotion)
- Cost: Standard replica cost + data transfer
- Catch: Replication lag can spike, no automatic failover
EC2 Multi-Region:
- Best for: Custom requirements, cost optimization
- RPO: Depends on your setup
- RTO: Depends on your automation
- Cost: Lowest (just compute + data transfer)
- Catch: You own all the complexity
Backup and Disaster Recovery
Backup Feature Matrix
| Feature | Aurora | RDS | EC2 |
|---|---|---|---|
| Automated Backups | Yes (continuous) | Yes (daily) | DIY |
| Backup Retention | 1-35 days | 0-35 days | DIY |
| Point-in-Time Recovery | Yes (1 sec) | Yes (5 min) | DIY |
| Backup Storage Cost | Free (< DB size) | Free (< DB size) | S3 costs |
| Cross-Region Backup | Yes (automated) | Yes (automated) | DIY |
| Restore Time (100GB) | 5-15 minutes | 10-30 minutes | Varies |
| Backup Impact on Perf | Zero | Minimal | Depends |
Operational Complexity
Daily Operations Comparison
| Operation | Aurora | RDS | EC2 |
|---|---|---|---|
| Monitoring | CloudWatch (built-in) | CloudWatch (built-in) | You configure everything |
| Patching | Zero-downtime for replicas | Maintenance window required | Your schedule, your responsibility |
| Scaling Vertical | Some downtime | Downtime required | Manual or scripted |
| Scaling Horizontal | Add replicas easily | Add replicas easily | Manual replication setup |
| Backup Management | Automatic | Automatic | You build it |
| Configuration | Managed by AWS | Managed by AWS | Full manual control |
Time Investment (Monthly Estimate)
| Task | Aurora | RDS | EC2 |
|---|---|---|---|
| Monitoring/Alerting Setup | 2 hours | 4 hours | 20 hours |
| Patching | 1 hour (review) | 2 hours | 4-8 hours |
| Backup Management | 0 hours | 0 hours | 2-4 hours |
| Performance Tuning | 2-4 hours | 2-4 hours | 8-16 hours |
| DR Testing | 2 hours | 4 hours | 8-12 hours |
| Incident Response | Low effort | Low effort | High effort |
| Total Monthly Ops | ~10 hours | ~15 hours | ~40-60 hours |
Cost of Your Time:
- If you're paid $100/hour, EC2 costs an extra $4,000-6,000/month in ops time
- Aurora/RDS save ~30-50 hours/month per DBA
The Decision Matrix
Quick Decision Guide: Which Option is Right for You?
| Your Situation | Choose This | Why |
|---|---|---|
| Need global replication (< 1s lag) | Aurora | Only option with Global Database |
| Need 15+ read replicas | Aurora | RDS limited to 5 replicas |
| Need fastest failover (< 1 min) | Aurora | 30-60s vs 60-120s (RDS) |
| Building financial/gaming platform | Aurora | Best reliability and performance |
| Cost-sensitive, predictable budget | RDS | No I/O surprises, lower cost |
| Standard PostgreSQL features | RDS | Vanilla PostgreSQL, widely compatible |
| Small team, no dedicated DBAs | RDS | Best effort/cost ratio |
| Migrating from on-prem PostgreSQL | RDS | Easiest migration path |
| Need custom extensions | EC2 | Only option with full control |
| Have dedicated DBA team | EC2 | Can justify ops overhead |
| Need kernel/OS tuning | EC2 | Full system access required |
| Need multi-master writes | EC2 | Not available in Aurora/RDS |
| High consistent write I/O | RDS or EC2 | Aurora I/O costs explode |
| Budget extremely tight | EC2 | Lowest compute cost (+ ops time) |
The Simple Truth
Most teams should start with RDS PostgreSQL. It's the Goldilocks option: not too expensive, not too complex, not too limited.
Upgrade to Aurora when:
- You need global replication
- You're scaling beyond RDS capabilities
- Downtime becomes unacceptable
Use EC2 only if:
- You need specific extensions unavailable in RDS/Aurora
- You have dedicated DBA resources
- Cost optimization is critical AND you can quantify ops costs
Real-World Cost Comparison (2025)
Scenario: Medium SaaS App (500GB DB, Moderate Traffic)
Aurora Setup:
- 1x db.r6g.2xlarge writer: $1,168/mo
- 2x db.r6g.2xlarge readers: $2,336/mo
- Storage (500GB): $50/mo
- I/O (estimated 50M/mo): $10/mo
- Total: ~$3,564/month
RDS PostgreSQL Setup:
- 1x db.r6g.2xlarge primary (Multi-AZ): $1,344/mo
- 2x db.r6g.2xlarge read replicas: $1,344/mo
- Storage (500GB gp3): $57.50/mo
- Backup storage (500GB): Free
- Total: ~$2,745/month
EC2 Self-Managed Setup:
- 3x r6g.2xlarge instances: $732/mo
- EBS storage (3x 500GB gp3): $120/mo
- Backup to S3 (500GB): $11.50/mo
- Data transfer: $50/mo (estimate)
- Your ops time: $4,000-6,000/mo (hidden cost)
- Total: ~$913/month + ops costs
The Reality: EC2 looks cheaper until you factor in ops time. Aurora looks expensive until you need global replication.
Extensions and Compatibility
PostgreSQL Extension Support
| Extension | Aurora | RDS | EC2 |
|---|---|---|---|
| PostGIS | ✅ Supported | ✅ Supported | ✅ Full control |
| pg_partman | ✅ Supported | ✅ Supported | ✅ Full control |
| TimescaleDB | ❌ Not supported | ❌ Not supported | ✅ Install manually |
| pgvector | ✅ Supported | ✅ Supported | ✅ Full control |
| pg_cron | ✅ Supported | ✅ Supported | ✅ Full control |
| Custom Extensions | ❌ Limited | ❌ Limited | ✅ Full control |
The Extension Problem: If you need TimescaleDB, Citus, or custom extensions, EC2 is your only option.
Migration Path
How Hard Is It to Switch?
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Migration Difficulty:
- Aurora ↔ RDS: Easy (logical dump/restore or snapshot restore)
- RDS → EC2: Moderate (pg_dump or continuous replication)
- EC2 → RDS/Aurora: Moderate (pg_dump or AWS DMS)
- Aurora → EC2: Hard (no direct path, requires logical dump)
Lock-in Risk: Aurora Global Database features create the strongest lock-in. RDS is fairly portable.
The Verdict: Decision Framework
Quick Decision Tree
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The Pragmatic Choice Matrix
| Your Situation | Recommendation | Why |
|---|---|---|
| Startup (< 10 people) | RDS PostgreSQL | Lower cost, minimal ops overhead |
| Startup (rapid global growth) | Aurora | Scale globally without re-arch |
| Mid-size (dedicated ops team) | RDS or EC2 | Depends on cost sensitivity |
| Enterprise (global presence) | Aurora Global DB | Best HA and global replication |
| Cost-constrained (skilled team) | EC2 | Lowest compute cost |
| Cost-constrained (no DBA) | RDS | Best cost/effort ratio |
| Need custom extensions | EC2 | No other option |
| Financial/Gaming | Aurora | Low latency, fast failover |
The Uncomfortable Truths
What AWS Won't Tell You
Aurora:
- I/O costs can spiral out of control on write-heavy workloads
- Still single-master (no active-active writes)
- Some PostgreSQL features lag behind vanilla PostgreSQL
- Global Database costs 2x per secondary region
RDS:
- Patching requires downtime for primary
- Can't tune kernel/OS parameters
- Some extensions not available
- Limited instance type choices compared to EC2
EC2:
- You're on your own for HA, backups, monitoring
- Hidden costs: ops time, incident response, complexity
- No fast failover without significant engineering
- You'll get paged at 3am
Future Considerations
Things That Might Change
Watch out for:
- Aurora I/O-Optimized: New pricing model (fixed I/O cost) launching soon
- RDS Blue/Green Deployments: Reduces patching downtime
- Aurora Serverless v3: Better scaling characteristics
- PostgreSQL 17+: New features may not reach RDS/Aurora immediately
- EC2 Graviton4: New instance types with better price/performance
The Warning: Cloud pricing and features change rapidly. What's true today may be outdated in 6 months. Always:
- Check current AWS pricing calculator
- Validate features in documentation
- Test in your environment before committing
- Monitor your actual costs vs. estimates
Conclusion: There Is No Perfect Answer
If you're optimizing for cost and have skilled DBAs: EC2 wins (but factor in ops costs)
If you're optimizing for reliability and global scale: Aurora wins (but watch those I/O bills)
If you're optimizing for simplicity and good-enough performance: RDS wins (the boring, reliable choice)
The Real Answer: Most teams should start with RDS PostgreSQL. It's the Goldilocks option: not too expensive, not too complex, not too limited.
Migrate to Aurora when:
- You need global replication
- You're scaling beyond RDS capabilities
- Downtime becomes unacceptable
Migrate to EC2 when:
- You need specific extensions
- You have dedicated DBA resources
- Cost optimization is critical
Remember: The best database is the one that lets your team ship features, not the one with the best benchmark numbers.
Additional Resources
- AWS Aurora Pricing Calculator
- AWS RDS Pricing
- EC2 Pricing
- Aurora vs RDS Official Comparison
- PostgreSQL Official Documentation
Still confused? That's normal. Database decisions are complex. Start with RDS, monitor your actual usage patterns, and optimize later when you have real data.
Remember: Premature optimization is the root of all evil, but so is ignoring a $10,000/month Aurora bill because you didn't understand I/O pricing.