Cloud Database Comparison: AWS vs GCP vs Azure 2025 Complete Review

"Should we use AWS, GCP, or Azure?" This is probably the most common question when enterprises move to cloud. Especially for databases—choosing wrong is extremely troublesome to change.

This article will deeply compare database services across the three major cloud platforms. Not just spec sheet comparisons, but actual usage differences, pricing calculations, and which to choose in what situations. After reading this, you should be able to make a better decision.

Further reading: Cloud Database Complete Guide | Understand cloud database basics

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Three Major Cloud Platform Database Service Overview

Let's look at the big picture first. All three platforms have complete database product lines, but each has its strengths.

AWS Database Service Ecosystem

AWS has the most complete database services—the most choices, and also the most complex.

Service Name	Type	Primary Use
RDS	Relational	MySQL, PostgreSQL, Oracle, SQL Server managed
Aurora	Relational	AWS-developed high-performance database
DynamoDB	NoSQL	Key-value/document database, millisecond latency
DocumentDB	Document	MongoDB compatible
ElastiCache	Cache	Redis, Memcached managed
Redshift	Data Warehouse	PB-scale analytical queries
Neptune	Graph	Social networks, recommendation systems
Timestream	Time-series	IoT, monitoring data
Keyspaces	Wide-column	Cassandra compatible
MemoryDB	In-memory	Redis compatible, persistent

AWS's advantage is "having everything." Whatever type of database you need, AWS probably has a corresponding service. The downside is too many choices—beginners can easily get lost.

GCP Database Service Ecosystem

Google Cloud has fewer database services, but each is distinctive.

Service Name	Type	Primary Use
Cloud SQL	Relational	MySQL, PostgreSQL, SQL Server managed
Cloud Spanner	NewSQL	Globally distributed, strongly consistent
Firestore	NoSQL	Real-time sync, mobile apps
Bigtable	Wide-column	PB-scale big data analytics
Memorystore	Cache	Redis, Memcached managed
BigQuery	Data Warehouse	Serverless analytical queries
AlloyDB	Relational	PostgreSQL-compatible high performance

GCP's highlights are Spanner (global consistency) and BigQuery (superb analytics). If you need these two features, GCP has virtually no substitutes.

Want to learn more about GCP databases? See: Google Cloud Database Detailed Tutorial

Azure Database Service Ecosystem

Azure is particularly friendly to enterprise customers, especially companies already using Microsoft products.

Service Name	Type	Primary Use
Azure SQL Database	Relational	SQL Server fully managed
Azure SQL Managed Instance	Relational	SQL Server high compatibility
Azure Database for MySQL	Relational	MySQL managed
Azure Database for PostgreSQL	Relational	PostgreSQL managed (including Hyperscale)
Cosmos DB	Multi-model	Globally distributed NoSQL
Azure Cache for Redis	Cache	Redis managed
Azure Synapse Analytics	Data Warehouse	Integrated analytics platform

Azure's strengths are SQL Server compatibility (it's Microsoft's own product) and Cosmos DB (multi-model NoSQL). Enterprises already with Microsoft 365 or Dynamics usually get better Azure contract terms.

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Relational Database Service Comparison

Relational databases are the core of most applications. Let's see how the three platforms' flagship services compare.

AWS RDS vs GCP Cloud SQL vs Azure SQL Database

These three are the most commonly compared services:

Comparison Item	AWS RDS	GCP Cloud SQL	Azure SQL Database
Supported Engines	MySQL, PostgreSQL, MariaDB, Oracle, SQL Server	MySQL, PostgreSQL, SQL Server	SQL Server (native)
Max Storage	64 TB	64 TB	100 TB
Max RAM	1 TB+	624 GB	4 TB
Read Replicas	Up to 15	Up to 10	Up to 4
Cross-region Replication	✅	✅	✅
Auto Backup	Up to 35 days	Up to 365 days	Up to 35 days
Serverless	Aurora Serverless	Cloud SQL Serverless (preview)	Azure SQL Serverless

AWS RDS advantage is mature stability, supporting the most engines. If you use Oracle or want multiple engine choices, RDS is the only option. Aurora is the evolved RDS—better performance but higher price.

GCP Cloud SQL advantage is simplicity and good integration with other Google services. Backup retention can go up to 365 days—stronger than the other two.

Azure SQL Database advantage is native SQL Server support. If your application already uses SQL Server, migration to Azure is smoothest.

MySQL Support Comparison

MySQL is the most used open-source database—all three platforms support it. Detailed MySQL integration tutorial: MySQL Cloud Integration Complete Guide

Comparison Item	AWS RDS for MySQL	GCP Cloud SQL for MySQL	Azure Database for MySQL
MySQL Version	5.7, 8.0	5.7, 8.0	5.7, 8.0
Auto Upgrade	✅	✅	✅
InnoDB Support	✅	✅	✅
Max Connections	Spec-dependent (max 16,000)	Spec-dependent (max 4,000)	Spec-dependent (max 5,000)
Slow Query Log	✅	✅	✅
Performance Insights	✅ (RDS)	Cloud SQL Insights	Query Performance Insight

In practice, MySQL support differences are minimal across all three. Choice mainly depends on which cloud platform's other services you use, and pricing.

PostgreSQL Support Comparison

PostgreSQL has become increasingly popular, with more powerful features than MySQL.

Comparison Item	AWS RDS for PostgreSQL	GCP Cloud SQL for PostgreSQL	Azure Database for PostgreSQL
PostgreSQL Version	12-16	12-16	12-16
Extension Support	80+	60+	40+
Logical Replication	✅	✅	✅
pgvector (Vector Search)	✅	✅	✅
Hyperscale/Citus	❌	❌	✅ (Flexible Server)

Azure's PostgreSQL has Hyperscale option (based on Citus), suitable for ultra-large scale data sharding. AWS and GCP have more extension support.

Performance and Availability Comparison

Comparison Item	AWS	GCP	Azure
Single-region SLA	99.95%	99.95%	99.99%
Multi-region SLA	99.99%	99.99%	99.995%
Auto Failover	✅	✅	✅
Zero-downtime Maintenance	Partial	✅	✅
Performance Tier Options	By instance type	By vCPU/RAM	By DTU or vCore

Azure SQL Database has the best SLA numbers, but in actual use all three are very stable. Don't fixate too much on SLA number differences when choosing.

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NoSQL Database Service Comparison

NoSQL suits applications needing high scalability and flexible schema. The three platforms' flagship NoSQL services each have characteristics.

AWS DynamoDB vs GCP Firestore vs Azure Cosmos DB

Comparison Item	AWS DynamoDB	GCP Firestore	Azure Cosmos DB
Data Model	Key-value/Document	Document	Multi-model (Document, Key-value, Graph, Wide-column)
Consistency Model	Eventual/Strong	Strong	5 consistency levels selectable
Global Distribution	Global Tables	Multi-region	Turnkey global distribution
Serverless	✅ (native)	✅ (native)	✅
Real-time Sync	Streams	✅ (native)	Change Feed
Transaction Support	✅ (limited)	✅	✅
Query Language	PartiQL	SQL-like	SQL API, MongoDB API, etc.

DynamoDB is AWS's flagship NoSQL—extremely good performance, completely serverless. Downside is less query flexibility; data modeling needs forethought.

Firestore is the first choice for mobile apps—real-time sync is superb. But complex query capability is limited, not suitable for large-scale data analytics.

Cosmos DB is the most flexible, supporting multiple data models and APIs. Downsides are higher price and more complex configuration.

Use Case Analysis

Choose DynamoDB when:

• Already in AWS ecosystem
• Need extremely low latency (single-digit milliseconds)
• Access patterns are clear, can be pre-designed

Choose Firestore when:

• Developing mobile apps (iOS, Android, Flutter)
• Need real-time sync features
• Small team, want rapid development

Choose Cosmos DB when:

• Need multiple data models
• Need globally distributed deployment
• Already in Azure ecosystem
• Have budget (Cosmos DB is pricier)

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Pricing Comparison

Pricing is one of the most important considerations when choosing cloud services. But cloud pricing is complex—same specs can cost very differently across platforms.

Billing Model Differences

The three platforms have different billing logic:

AWS RDS:

• Billed by instance type (db.t3.micro, db.r5.large, etc.)
• Storage billed separately (GP2, GP3, Provisioned IOPS)
• Can buy Reserved Instances to save (1 or 3 years)

GCP Cloud SQL:

• Billed by vCPU + memory
• Storage billed separately (SSD or HDD)
• Can use Committed Use Discount (1 or 3 years)

Azure SQL Database:

• DTU mode (simple but not transparent)
• vCore mode (similar to AWS/GCP)
• Serverless mode (auto-scales)
• Reserved Capacity for savings

Same-Spec Cost Calculation

For a medium application (4 vCPU, 16GB RAM, 500GB SSD, single region):

Platform	Service	Estimated Monthly (USD)
AWS	RDS db.r6g.xlarge + 500GB GP3	~$350-400
GCP	Cloud SQL (4 vCPU, 16GB)	~$300-350
Azure	Azure SQL vCore (4 vCore)	~$400-450

Note: This is rough estimate only—actual prices vary by region, discounts, network traffic, etc. Use each platform's pricing calculator.

Money-saving tips:

1. Buy 1 or 3-year commitment—save 30-60%
2. Use smaller specs for dev environments; can turn off at night
3. Leverage free tiers (see next section)
4. Regularly review for idle resources

Free Tier Comparison

Detailed free plan comparison: Free Cloud Database Complete List

Platform	Relational DB Free Tier	NoSQL Free Tier
AWS	RDS 750 hours/month (12 months)	DynamoDB 25GB (permanent)
GCP	Cloud SQL none ($300 trial credit)	Firestore 1GB + 50K reads/day (permanent)
Azure	SQL Database 250GB (12 months)	Cosmos DB 1000 RU/s + 25GB (permanent)

AWS and Azure have better relational database free tiers; GCP's Firestore free tier is very generous.

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Pricing is just part of the choice. Architecture design, team familiarity, and future scalability all matter. Schedule free consultation and let us help with comprehensive assessment.

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Feature Comparison

Beyond basic features, some advanced capabilities may influence your choice.

Auto-scaling Capability

Platform	Vertical Scaling	Horizontal Scaling	Serverless
AWS	Requires downtime (Multi-AZ reduces)	Aurora Auto Scaling	Aurora Serverless v2
GCP	Requires downtime	Cloud Spanner native	Cloud SQL Serverless (preview)
Azure	Online scaling (vCore)	Hyperscale	Azure SQL Serverless

Azure SQL Database does online vertical scaling best—almost no downtime. AWS Aurora Serverless v2 is more mature in the serverless space.

Backup and Disaster Recovery

Platform	Auto Backup	Retention	Cross-region Backup	Point-in-time Recovery
AWS	✅	Max 35 days	✅ (needs config)	✅
GCP	✅	Max 365 days	✅	✅
Azure	✅	Max 35 days	✅	✅

GCP Cloud SQL has the longest backup retention—up to 365 days. If you have compliance requirements for long-term backup retention, this is an advantage.

Security and Compliance Certifications

All three platforms meet mainstream compliance certifications:

Certification	AWS	GCP	Azure
ISO 27001	✅	✅	✅
SOC 1/2/3	✅	✅	✅
PCI DSS	✅	✅	✅
HIPAA	✅	✅	✅
FedRAMP	✅	✅	✅

Security-wise all three are comprehensive. The key is correctly configuring encryption, access control, network isolation, etc.

Monitoring and Management Tools

Feature	AWS	GCP	Azure
Performance Monitoring	Performance Insights	Cloud SQL Insights	Query Performance Insight
Slow Query Analysis	✅	✅	✅
Alert Configuration	CloudWatch Alarms	Cloud Monitoring	Azure Monitor
Optimization Recommendations	Trusted Advisor	Recommender	Advisor
Cost Analysis	Cost Explorer	Cost Management	Cost Management

AWS Performance Insights is the most powerful for deep database performance analysis. GCP and Azure tools are sufficient but not as detailed as AWS.

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Selection Recommendations: By Scenario

After all these comparisons, which should you choose? Here are specific recommendations.

Startup Recommendations

Limited budget, want rapid development: → GCP (Firebase + Cloud SQL)

• Firebase has generous free tier, fast development
• Cloud SQL is simple and easy
• $300 trial credit can last a while

Need maximum flexibility, preparing for rapid scaling: → AWS

• Most complete services—has everything
• Largest community resources, easy to find answers
• Most expansion options in future

Enterprise Application Recommendations

Already Microsoft ecosystem: → Azure

• Good integration with Microsoft 365, Dynamics
• Smoothest SQL Server migration
• EA contracts usually have discounts

Need global deployment, strong consistency: → GCP Cloud Spanner or Azure Cosmos DB

• These two lead in globally distributed databases
• Banking, finance, and other strong consistency scenarios

Need most stable, most mature solution: → AWS RDS / Aurora

• Highest market share, most pitfalls discovered
• Richest documentation and community resources

Already on Specific Platform Recommendations

If you're already using other services on a platform (compute, storage, networking), strongly recommend using the same provider for databases:

• Same-platform advantages: Low network latency, free data transfer, simple integration
• Cross-platform disadvantages: High network costs, increased latency, complex permission management

Unless there's a very clear reason, don't go cross-platform for databases.

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FAQ

Which cloud database is cheapest?

No absolute answer—depends on your use case. Roughly:

• Small applications: GCP is usually slightly cheaper
• Medium applications: All three are similar
• Large applications: Contract pricing—whoever gives bigger discounts

Recommend using each platform's pricing calculator, then add at least 20% buffer (network traffic, backup fees are easily underestimated).

Can I use databases across clouds?

Technically yes, but not recommended. Cross-cloud issues:

• Increased network latency (cross-platform uses public internet)
• High data transfer fees
• Increased operations complexity
• Increased security risks

If you truly need multi-cloud, consider cross-cloud databases like CockroachDB or TiDB.

Is migrating to another platform difficult?

Depends on what you're using:

Relatively easy to migrate:

• Standard engines like MySQL, PostgreSQL
• Only using basic SQL features

Harder to migrate:

• Using platform-specific features (Aurora-specific, Cosmos DB proprietary APIs)
• Heavy stored procedure usage
• Deep integration with other services

Recommend considering portability during design phase. Use standard SQL, avoid over-relying on proprietary features.

Do the three platforms have data centers in Taiwan?

• AWS: No (nearest are Tokyo, Singapore)
• GCP: Yes (Taiwan Changhua)
• Azure: Yes (Taiwan)

If you have data residency requirements (e.g., government projects or financial regulations), GCP and Azure have advantages.

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Conclusion

AWS, GCP, Azure—all three platforms have mature database services. There's no absolute good or bad. Selection keys are:

1. What platform are you on now? Same platform is usually best
2. What's your team familiar with? Learning curve is also a cost
3. Any special requirements? E.g., global distribution, data residency
4. What's your budget? Remember to calculate long-term costs

Quick Recommendations

Scenario	Recommended Platform
Startup rapid development	GCP
Enterprise stable operations	AWS or Azure
Microsoft ecosystem	Azure
Globally distributed needs	GCP Spanner or Azure Cosmos DB
Most service choices	AWS
Taiwan data residency	GCP or Azure

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AWS vs GCP vs Azure—Which to Choose?

Every platform has pros and cons—the key is finding the best fit for your business.

But "best fit" isn't just about spec sheets. You need to consider:

• Integration difficulty with existing systems
• Team learning costs
• Expansion needs for next 3-5 years
• Total Cost of Ownership (TCO)

CloudInsight Free Cloud Consultation can help you:

✅ Needs analysis: Understand your business requirements, identify key considerations ✅ Platform comparison: Objectively compare platform pros/cons for your scenario ✅ Cost calculation: Estimate actual costs per platform, including hidden fees ✅ Migration planning: If platform change needed, plan lowest-risk migration path

Schedule Free Consultation

Click to schedule 30-minute free consultation

We're AWS Partner and Google Cloud Partner—we can give you objective, neutral advice.

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Further Reading

• Cloud Database Complete Guide
• Free Cloud Database Complete List
• MySQL Cloud Database Integration Guide
• Google Cloud Database Detailed Tutorial

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References

1. AWS Database Services Overview - Amazon Web Services
2. Google Cloud Database Products - Google Cloud Platform
3. Azure Database Services - Microsoft Azure
4. Gartner Magic Quadrant for Cloud Database Management Systems 2024
5. DB-Engines Ranking - Cloud Database Trend
6. AWS vs Azure vs GCP - Cloud Comparison 2025