Database Comparison - Detailed Analysis¶

Comprehensive comparison of GCP database services to help you choose the right solution.

📋 Table of Contents¶

Overview
Feature Comparison
Performance Comparison
Cost Comparison
Use Case Matrix
Migration Paths
Decision Framework

Overview¶

Database Services Summary¶

Service	Type	Best For	Starting Price
Cloud SQL	Relational	Traditional apps	$15/month
Cloud Spanner	Relational	Global apps	$657/month
Firestore	Document	Mobile/web apps	$1/month
Bigtable	Wide-column	Analytics, IoT	$474/month
Memorystore	Key-value	Caching	$35/month

Feature Comparison¶

Data Model¶

Feature	Cloud SQL	Cloud Spanner	Firestore	Bigtable	Memorystore
Data Model	Tables/Rows	Tables/Rows	Collections/Docs	Row/Column	Key-Value
Schema	Fixed	Fixed	Flexible	Flexible	None
Query Language	SQL	SQL	NoSQL	NoSQL	Commands
Joins	Yes	Yes	No	No	No
Transactions	ACID	ACID	ACID	Single-row	No
Indexes	Yes	Yes	Yes	No	No

Scalability¶

Feature	Cloud SQL	Cloud Spanner	Firestore	Bigtable	Memorystore
Scaling Type	Vertical	Horizontal	Automatic	Horizontal	Vertical
Max Size	64 TB	Unlimited	Unlimited	Petabytes	300 GB
Max QPS	10K	100K+	10K	1M+	1M+
Auto-scaling	Storage only	Yes	Yes	Yes	No
Read Replicas	Yes	Yes	No	Yes	Yes (Standard)

Availability¶

Feature	Cloud SQL	Cloud Spanner	Firestore	Bigtable	Memorystore
SLA	99.95%	99.999%	99.99%	99.9%	99.9%
Multi-region	No	Yes	Yes	No	No
Automatic Failover	Yes	Yes	N/A	Yes	Yes (Standard)
Backup	Yes	Yes	No	Yes	No
Point-in-time Recovery	Yes	Yes	No	No	No

Performance¶

Feature	Cloud SQL	Cloud Spanner	Firestore	Bigtable	Memorystore
Read Latency	5-10ms	5-10ms	10-20ms	<10ms	<1ms
Write Latency	5-10ms	5-10ms	10-20ms	<10ms	<1ms
Consistency	Strong	Strong	Strong	Eventual	Strong
Throughput/Node	10K QPS	10K QPS	N/A	10K QPS	100K+ QPS

Integration¶

Feature	Cloud SQL	Cloud Spanner	Firestore	Bigtable	Memorystore
BigQuery	Yes	Yes	Yes	Yes	No
Dataflow	Yes	Yes	Yes	Yes	No
Cloud Functions	Yes	Yes	Yes	Yes	Yes
App Engine	Yes	Yes	Yes	Yes	Yes
GKE	Yes	Yes	Yes	Yes	Yes
Mobile SDKs	No	No	Yes	No	No

Performance Comparison¶

Latency Benchmarks¶

Read Latency (p50):
Memorystore: ▓ 0.5ms
Bigtable:    ▓▓▓▓▓ 5ms
Cloud SQL:   ▓▓▓▓▓▓ 6ms
Spanner:     ▓▓▓▓▓▓▓ 7ms
Firestore:   ▓▓▓▓▓▓▓▓▓▓ 10ms

Write Latency (p50):
Memorystore: ▓ 0.5ms
Bigtable:    ▓▓▓▓▓ 5ms
Cloud SQL:   ▓▓▓▓▓▓▓ 7ms
Spanner:     ▓▓▓▓▓▓▓▓ 8ms
Firestore:   ▓▓▓▓▓▓▓▓▓▓▓▓ 12ms

Throughput Comparison¶

Database	Single Node QPS	10 Nodes QPS	Scaling
Memorystore	1M+	N/A	Vertical
Bigtable	10K	100K	Linear
Cloud Spanner	10K	100K	Linear
Cloud SQL	10K	100K (replicas)	Vertical + Replicas
Firestore	10K	N/A	Automatic

Storage Performance¶

Database	IOPS/GB	Throughput	Storage Type
Cloud SQL (SSD)	30	480 MB/s	Block
Cloud SQL (HDD)	1.5	120 MB/s	Block
Cloud Spanner	High	High	Distributed
Firestore	N/A	N/A	Document
Bigtable (SSD)	Very High	Very High	Columnar
Bigtable (HDD)	Medium	Medium	Columnar
Memorystore	Extreme	Extreme	Memory

Cost Comparison¶

Small Application (Development)¶

Requirements: - 10 GB storage - 1,000 QPS - Single region - Development workload

Database	Configuration	Monthly Cost
Cloud SQL	db-f1-micro, 10 GB	$15
Firestore	1 GB, 100K reads/day	$1
Memorystore	1 GB Redis Basic	$35
Bigtable	1 node (dev)	$47 (HDD)
Cloud Spanner	100 PUs	$66

Winner: Firestore ($1/month)

Medium Application (Production)¶

Requirements: - 100 GB storage - 10,000 QPS - High availability - Production workload

Database	Configuration	Monthly Cost
Cloud SQL	db-n1-standard-4, 100 GB, HA	$500
Firestore	10 GB, 1M reads/day	$10
Memorystore	5 GB Redis Standard	$281
Bigtable	3 nodes SSD	$1,422
Cloud Spanner	3 nodes	$1,971

Winner: Firestore ($10/month) for document data, Cloud SQL ($500/month) for relational

Large Application (Enterprise)¶

Requirements: - 1 TB storage - 100,000 QPS - Multi-region - Enterprise workload

Database	Configuration	Monthly Cost
Cloud SQL	db-n1-highmem-16, 1 TB, replicas	$3,000+
Firestore	100 GB, 10M reads/day	$100
Memorystore	100 GB Redis Standard	$5,616
Bigtable	10 nodes SSD	$4,740
Cloud Spanner	10 nodes multi-region	$7,300

Winner: Depends on requirements (Firestore for document, Bigtable for analytics)

Cost Per Operation¶

Database	Read Cost	Write Cost	Storage Cost
Cloud SQL	Included	Included	$0.17/GB (SSD)
Cloud Spanner	Included	Included	$0.30/GB
Firestore	$0.06/100K	$0.18/100K	$0.18/GB
Bigtable	Included	Included	$0.17/GB (SSD)
Memorystore	Included	Included	$35-56/GB

Use Case Matrix¶

Web Applications¶

Requirement	Recommended	Alternative	Reason
Traditional CRUD	Cloud SQL	Cloud Spanner	SQL support, ACID
Global users	Cloud Spanner	Firestore	Multi-region, consistency
Session storage	Memorystore	Firestore	Low latency
User profiles	Firestore	Cloud SQL	Flexible schema
Shopping cart	Memorystore	Firestore	Fast access

Mobile Applications¶

Requirement	Recommended	Alternative	Reason
User data	Firestore	Cloud SQL	Offline support, SDKs
Real-time chat	Firestore	Bigtable	Real-time sync
Analytics	Bigtable	BigQuery	High throughput
Leaderboards	Memorystore	Cloud Spanner	Low latency
Content	Firestore	Cloud SQL	Flexible schema

Analytics & IoT¶

Requirement	Recommended	Alternative	Reason
Time-series data	Bigtable	Cloud SQL	Scale, performance
IoT telemetry	Bigtable	Firestore	High throughput
Clickstream	Bigtable	BigQuery	Real-time ingestion
Logs	Bigtable	BigQuery	High volume
Metrics	Bigtable	Cloud SQL	Fast writes

Financial Services¶

Requirement	Recommended	Alternative	Reason
Transactions	Cloud Spanner	Cloud SQL	Global ACID
Trading data	Bigtable	Cloud Spanner	Low latency
User accounts	Cloud SQL	Cloud Spanner	ACID, SQL
Audit logs	Bigtable	Cloud SQL	Immutable
Real-time pricing	Memorystore	Bigtable	Sub-ms latency

Gaming¶

Requirement	Recommended	Alternative	Reason
Player profiles	Firestore	Cloud SQL	Flexible schema
Leaderboards	Memorystore	Cloud Spanner	Low latency
Game state	Firestore	Memorystore	Real-time sync
Analytics	Bigtable	BigQuery	High volume
Matchmaking	Memorystore	Cloud Spanner	Fast access

Migration Paths¶

From MySQL/PostgreSQL¶

Current: MySQL/PostgreSQL
    |
    ├─> Cloud SQL (Lift & Shift)
    │   - Minimal changes
    │   - Quick migration
    │   - Same features
    │
    ├─> Cloud Spanner (Modernize)
    │   - Schema changes required
    │   - Global scale
    │   - Higher cost
    │
    └─> Firestore (Replatform)
        - Application rewrite
        - NoSQL model
        - Lower cost

From MongoDB¶

Current: MongoDB
    |
    ├─> Firestore (Similar model)
    │   - Document database
    │   - Managed service
    │   - Real-time features
    │
    ├─> Bigtable (Scale)
    │   - Higher throughput
    │   - Different model
    │   - Analytics workloads
    │
    └─> Cloud SQL (Relational)
        - Schema required
        - SQL queries
        - ACID transactions

From Cassandra/HBase¶

Current: Cassandra/HBase
    |
    ├─> Bigtable (Direct migration)
    │   - HBase API compatible
    │   - Similar model
    │   - Managed service
    │
    ├─> Cloud Spanner (Relational)
    │   - SQL support
    │   - ACID transactions
    │   - Schema required
    │
    └─> Firestore (Document)
        - Flexible schema
        - Real-time features
        - Lower throughput

From Redis/Memcached¶

Current: Redis/Memcached
    |
    ├─> Memorystore (Lift & Shift)
    │   - Same API
    │   - Managed service
    │   - No changes
    │
    ├─> Firestore (Persistent)
    │   - Durable storage
    │   - Flexible schema
    │   - Higher latency
    │
    └─> Bigtable (Scale)
        - Higher throughput
        - Persistent storage
        - Different API

Decision Framework¶

Step 1: Data Model¶

What type of data?
    |
    ├─> Structured + SQL → Cloud SQL or Cloud Spanner
    ├─> Document/JSON → Firestore
    ├─> Time-series → Bigtable
    └─> Key-value → Memorystore

Step 2: Scale Requirements¶

Expected scale?
    |
    ├─> < 1 TB, < 10K QPS → Cloud SQL
    ├─> < 10 TB, < 100K QPS → Cloud Spanner or Bigtable
    ├─> > 10 TB, > 100K QPS → Bigtable
    └─> Caching → Memorystore

Step 3: Geographic Distribution¶

Geographic requirements?
    |
    ├─> Single region → Cloud SQL, Bigtable, Memorystore
    ├─> Multi-region → Cloud Spanner, Firestore
    └─> Global → Cloud Spanner

Step 4: Consistency Requirements¶

Consistency needs?
    |
    ├─> Strong consistency + SQL → Cloud SQL or Cloud Spanner
    ├─> Strong consistency + NoSQL → Firestore
    ├─> Eventual consistency → Bigtable
    └─> No persistence → Memorystore

Step 5: Budget¶

Budget constraints?
    |
    ├─> < $100/month → Firestore or Cloud SQL (small)
    ├─> < $1,000/month → Cloud SQL or Firestore
    ├─> < $5,000/month → Bigtable or Cloud Spanner
    └─> > $5,000/month → Any service

Decision Matrix¶

If you need...	Choose...	Because...
SQL + Regional	Cloud SQL	Cost-effective, familiar
SQL + Global	Cloud Spanner	Multi-region, consistency
Document + Mobile	Firestore	SDKs, offline support
Time-series + Scale	Bigtable	Throughput, latency
Caching	Memorystore	Sub-ms latency
Flexible + Cheap	Firestore	Pay per operation
ACID + Scale	Cloud Spanner	Horizontal scaling
Analytics	Bigtable	High throughput

Hybrid Architectures¶

Pattern 1: SQL + Cache¶

Application
    |
    v
┌─────────────────┐
│  Memorystore    │ ← Cache layer
│  (Redis)        │
└────────┬────────┘
         │ Cache miss
         v
┌─────────────────┐
│  Cloud SQL      │ ← Primary database
│  (PostgreSQL)   │
└─────────────────┘

Use Case: Web application with frequent reads

Pattern 2: Relational + Document¶

Application
    |
    ├─> Cloud SQL (Transactions)
    │   - Orders
    │   - Payments
    │   - Inventory
    │
    └─> Firestore (User data)
        - Profiles
        - Preferences
        - Activity

Use Case: E-commerce with user profiles

Pattern 3: Operational + Analytics¶

Application
    |
    v
┌─────────────────┐
│  Cloud SQL      │ ← Operational
│  (OLTP)         │
└────────┬────────┘
         │ ETL
         v
┌─────────────────┐
│  Bigtable       │ ← Analytics
│  (OLAP)         │
└─────────────────┘

Use Case: Real-time analytics on operational data

Pattern 4: Multi-Database¶

Application
    |
    ├─> Cloud SQL (Core data)
    ├─> Firestore (User profiles)
    ├─> Bigtable (Analytics)
    └─> Memorystore (Cache)

Use Case: Large-scale application with diverse requirements

Summary¶

Quick Reference¶

Choose Cloud SQL when: - You need SQL - Regional deployment - Traditional application - Budget < $1,000/month

Choose Cloud Spanner when: - You need SQL + global scale - Strong consistency required - Multi-region deployment - Budget > $2,000/month

Choose Firestore when: - Document data model - Mobile/web application - Real-time features needed - Budget < $100/month

Choose Bigtable when: - Time-series data - High throughput required - Analytics workload - Budget > $1,000/month

Choose Memorystore when: - Caching layer - Sub-ms latency required - Session storage - Budget > $50/month

Next Steps¶

Best Practices - Production guidelines
Cloud SQL - Relational database details
Cloud Spanner - Global database details

Last Updated: March 2026
Status: ✅ Complete