MongoDB Multi-Tenancy Strategies

🎮 Control Panel

Select Tenant

Perform Operation

Activity Log

--:--:-- Ready. Select tenant & operation.

Database per Tenant ISOLATED

🔒 Isolation:

⚠️ WARNING: Query missing tenant_id filter!

📄

📈 Real-Time Performance Metrics

Query Latency

2ms

Ops/Second

12K/s

Memory Usage

2.4GB

Connections

450

Query Complexity

Low

Index Efficiency

95%

🔌 Connection Pool (Per-Tenant Pools)

💰 Cost Estimation (at 100 tenants)

🔌

Connections

~10,000

💾

Storage Overhead

High metadata

⚡

Compute

Moderate

🛠️

Mgmt Complexity

100 DBs to manage

📊

Index Storage

Duplicated indexes

💵

Est. Monthly

~$2,500

🔊 Noisy Neighbor Simulation

💡 What is Noisy Neighbor? When one tenant consumes excessive resources (CPU, I/O, connections), it can degrade performance for other tenants. Key insight: Logical isolation (separate DBs/collections) does NOT prevent this—only hardware isolation via sharding truly separates tenants onto different physical servers.

🏢

Tenant A

Normal operations

2ms

⟷

🏬

Tenant B

Normal operations

2ms

⟷

🏭

Tenant C

Normal operations

2ms

Shared Resource Usage

25%

Cross-Tenant Impact

None

Isolation Effectiveness

100%

📊 Current Strategy: Database per Tenant 🛡️ HIGH ISOLATION

With separate databases per tenant, each tenant has dedicated resources. A noisy neighbor cannot impact other tenants because they operate on completely isolated database instances.

🔄 Migration Path

🔗 Shared

→

📁 Collection

→

🗄️ Database

→

🌍 Zone Shard

💡 Start with Shared Collection for prototyping, migrate to Collection/Tenant as you grow, then to DB/Tenant for enterprise customers.

📊 Strategy Comparison

Aspect	DB/Tenant	Collection/Tenant	Shared	Zone Sharding	Range Sharding
Data Isolation
Horizontal Scale
Data Locality	Per DB	Per Collection	Mixed	🌍 By Region	📊 By Range
Compliance/GDPR	Manual	Manual	Complex	✅ Built-in	Possible
Best For	Enterprise	Mid-Market	Consumer	Global SaaS	Large Tenants