software
MongoDB vs PostgreSQL 2026: Database Comparison
PostgreSQL is a relational SQL database excelling at structured data with ACID compliance and complex queries, while MongoDB is a NoSQL document database optimized for flexible, unstructured data and horizontal scaling. The choice depends on your data structure and consistency requirements.
M
MongoDB
NoSQL document database for flexible, scalable applications with JSON-like data structures.
Real-time applications, content management systems, IoT data, rapid prototyping, applications requiring high write throughput and horizontal scaling
Score63%
VS
PostgreSQL
Open-source relational SQL database known for reliability, advanced features, and strong consistency.
Financial systems, e-commerce platforms, traditional business applications, data warehousing, applications requiring strict consistency and complex relational queries
Score63%
Quick Answer
AI SummaryPostgreSQL is a relational SQL database excelling at structured data with ACID compliance and complex queries, while MongoDB is a NoSQL document database optimized for flexible, unstructured data and horizontal scaling. The choice depends on your data structure and consistency requirements.
Our Verdict
AI-assistedChoose PostgreSQL if you have structured, relational data with complex queries, need guaranteed ACID compliance across all operations, and want lower hosting costs. Choose MongoDB if you need schema flexibility, rapid prototyping, massive horizontal scalability, or work with semi-structured/nested JSON data like real-time analytics or content management systems.
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M
MongoDB
6.2/10
PostgreSQL
8.8/10
M
Choose MongoDB if
Real-time applications, content management systems, IoT data, rapid prototyping, applications requiring high write throughput and horizontal scaling
Choose PostgreSQL if
Best pickFinancial systems, e-commerce platforms, traditional business applications, data warehousing, applications requiring strict consistency and complex relational queries
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Key Differences at a Glance
- Data Model:Document-based (JSON/BSON) vs Relational (Tables/Rows)
- Transaction Support:✓ PostgreSQL wins(Full ACID across all operations vs Multi-document ACID (v4.0+))
- Query Language:MongoDB Query Language (MQL) vs SQL
Key Facts & Figures
72 numeric metrics compared
| Metric | MongoDB | PostgreSQL | Ratio |
|---|---|---|---|
| Average Query Latency (structured data)(ms) | 8-12ms for equivalent queries | — | — |
| Memory Usage (100GB dataset)(GB) | 24-36GB working set | — | — |
| Years in Production(years) | 19 years (MongoDB 1.0 released 2009) | — | — |
| Write Throughput (single server)(operations/second) | 100,000-500,000 ops/sec | — | — |
| Community Popularity(% of developers) | 28% of web applications (Stack Overflow 2024) | — | — |
| Write Throughput (bulk inserts)(documents/second) | 50,000-100,000 docs/sec | 15,000-25,000 docs/sec | |
| Query Language Complexity (learning curve)(months) | 2-4 weeks (MongoDB Query Language simpler syntax) | 1-2 months (SQL standardized, widely taught) | |
| Memory Usage (100K documents)(MB) | 250-350 MB | 150-200 MB | |
| Index Types Supported(count) | 10+ (single field, compound, geospatial, text, wildcard) | 20+ (B-tree, hash, BRIN, GiST, partial indexes) | |
| Free Tier Storage(GB) | 0 GB (Atlas free tier discontinued) | — | — |
| Minimum Production Tier Cost(USD/month) | $57 | — | — |
| Annual npm Downloads (Drivers)(millions) | 21.7M | — | — |
| Baseline Latency(milliseconds) | 5-10ms (cluster dependent) | — | — |
| Minimum Monthly Cost (Production)(USD) | $57 (M10 Atlas cluster) | $20-50 (cloud VM minimum) | |
| Read Throughput (1TB dataset)(ops/second) | 10,000-50,000 ops/sec | — | — |
| Document Size Limit(MB) | 16 MB | — | — |
| Minimum Monthly Cost (Managed)(USD) | $57 | — | — |
| Time to Production Deployment(minutes) | 40-80 hours | — | — |
| Query Complexity (Aggregation Capability)(rating 1-10) | 9 (full aggregation pipeline) | — | — |
| Setup DevOps Requirement(hours/month) | 20-40 hours | — | — |
| Maximum Concurrent Connections(connections) | Unlimited (scales with cluster) | 1,000+ | — |
| Real-time Sync Implementation Effort(days) | 5-10 days (custom code) | — | — |
| Startup Monthly Cost(USD) | $57/month | — | — |
| Average Query Latency(milliseconds) | 10-50 ms | — | — |
| Free Tier Database Storage(GB) | 512 MB | — | — |
| Monthly Cost (Entry Paid Tier)(USD) | $57 | — | — |
| Query Response Time (Median)(ms) | 38 ms (indexed query) | — | — |
| Maximum Database Size (Free Tier)(GB) | 0.512 GB | — | — |
| Max Write Throughput (Optimized)(writes/second) | ~50,000 (sharded cluster) | ~10,000 (single node) | |
| Storage Overhead (vs Equivalent Relational)(multiple) | 2-3x larger (denormalization) | 1x baseline (normalized) | |
| Community Size & Ecosystem(relative rank) | ~25k stars | ~15k stars | |
| Typical Setup Complexity(time to production (hours)) | 4-8 hours (managed cloud option available) | 2-4 hours (widely supported, simpler setup) | |
| Starting Managed Hosting Cost(USD/month) | $57 (Atlas M10) | $15 (RDS free tier + $20) | |
| Storage Efficiency(% overhead) | 25-40% (document format, field duplication) | 5-15% (optimized row format) | |
| Join Performance on 1M+ rows(seconds) | 8-15+ seconds ($lookup) | 0.5-2 seconds (optimized joins) | |
| Extension Ecosystem(available extensions) | Limited (core features only) | 75+ community extensions | |
| Simple Query Throughput(queries/sec) | ~25,000 (PostgreSQL 18) | ~25,000 (PostgreSQL 18) | |
| Complex Join Performance(ms response time) | ~320 (5-table join) | ~320 (5-table join) | |
| Base Memory Footprint(MB) | ~150 (minimal config) | ~150 (minimal config) | |
| AWS RDS Managed Cost($/month (db.t3.micro, single-AZ)) | $15.25 (PostgreSQL 18) | $15.25 (PostgreSQL 18) | |
| Supported Versions (2026)(major versions) | 5 (14-18 active) | 5 (14-18 active) | |
| Replication Lag (typical)(ms) | 10-100 (WAL) | 10-100 (WAL) | |
| Single-Node Write Throughput(writes/sec) | 35,000 writes/sec | 35,000 writes/sec | |
| Minimum Cluster Size(nodes) | 1 (single instance) | 1 (single instance) | |
| PostgreSQL SQL Compatibility(percent) | 100% (native) | 100% (native) | |
| Self-Hosted Cost (Base)(USD/month) | $0 (open-source) | $0 (open-source) | |
| GitHub Stars(stars) | 3,500+ stars | 3,500+ stars | |
| Production Maturity (Years Active)(years) | 25+ years | 25+ years | |
| Monthly Base Cost (Small Instance)(USD) | $0 (infrastructure cost only) | $0 (infrastructure cost only) | |
| Setup Time (Fresh Installation)(minutes) | 30-60 minutes | 30-60 minutes | |
| License Cost (Annual, Small Enterprise)(USD) | $0 | $0 | |
| Time to Production(days) | 120-1440 minutes (self-hosted) | 120-1440 minutes (self-hosted) | |
| Built-in Authentication Methods(methods) | 0 (requires third-party) | 0 (requires third-party) | |
| Maximum Database Size(items supported) | Unlimited (petabyte+ capable) | Unlimited (petabyte+ capable) | |
| Simple SELECT Query Speed(milliseconds (relative)) | 115-120ms | 115-120ms | |
| Minimum Monthly Cost(USD) | $0 (open-source) | $0 (open-source) | |
| Production Tier Monthly Base Cost(USD) | $0 (self-hosted only) | $0 (self-hosted only) | |
| Time to Deploy Production Database(minutes) | 240-1440 minutes (4-24 hours) | 240-1440 minutes (4-24 hours) | |
| Monthly Cost (100 GB, moderate traffic)(USD) | $50-200+ (self-hosted infrastructure) or $100-500 (managed provider) | $50-200+ (self-hosted infrastructure) or $100-500 (managed provider) | |
| Available PostgreSQL Extensions(count) | 500+ (all available from PostgreSQL ecosystem) | 500+ (all available from PostgreSQL ecosystem) | |
| Cold Start Latency(milliseconds) | 0 seconds (always running) | 0 seconds (always running) | |
| Community Size & Support(user base estimate) | 10,000,000+ deployments globally | 10,000,000+ deployments globally | |
| Complex Analytical Query Speed (with JOINs + aggregations)(milliseconds (relative)) | 320ms (with window functions) | 320ms (with window functions) | |
| Default Memory Usage(MB) | 300MB | 300MB | |
| Maximum JSON Document Size(GB) | 1GB+ (JSONB) | 1GB+ (JSONB) | |
| Full-Text Search Languages Supported(languages) | 15+ languages | 15+ languages | |
| Hosting Provider Compatibility(percent) | 85% of providers | 85% of providers | |
| Simple Query Speed (1M rows, SELECT *)(milliseconds) | 52ms (PostgreSQL) | 52ms (PostgreSQL) | |
| Complex Analytical Query Speed (Aggregate + Join)(milliseconds) | 850ms (PostgreSQL) | 850ms (PostgreSQL) | |
| Minimum Memory Requirement(MB) | 100MB | 100MB | |
| Maximum Connection Limit (Default)(connections) | 100 | 100 | |
| Developer Preference (2024 Survey)(%) | 44% | 44% |
Sourced from publicly available data ·
Key Differences
7 attributes compared head-to-head
M
2MongoDBPostgreSQL leads2 ties
MongoDB
Attribute
PostgreSQL
- Document-based (JSON/BSON)Data ModelRelational (Tables/Rows)
- Multi-document ACID (v4.0+)Transaction SupportFull ACID across all operations(winner)
- MongoDB Query Language (MQL)Query LanguageSQL
- Native sharding built-in(winner)Horizontal ScalingRequires third-party solutions
- Schema-less (dynamic)(winner)Schema FlexibilityFixed schema required
- $lookup (limited performance)Join OperationsNative joins (optimized)(winner)
- $57-300/month (Atlas M10-M30)Typical Deployment Cost$15-100/month (RDS/Managed)(winner)
- Data Model
MongoDB
Document-based (JSON/BSON)
PostgreSQL
Relational (Tables/Rows)
- Transaction Support
MongoDB
Multi-document ACID (v4.0+)
PostgreSQL
Full ACID across all operations(winner)
- Query Language
MongoDB
MongoDB Query Language (MQL)
PostgreSQL
SQL
- Horizontal Scaling
MongoDB
Native sharding built-in(winner)
PostgreSQL
Requires third-party solutions
- Schema Flexibility
MongoDB
Schema-less (dynamic)(winner)
PostgreSQL
Fixed schema required
- Join Operations
MongoDB
$lookup (limited performance)
PostgreSQL
Native joins (optimized)(winner)
- Typical Deployment Cost
MongoDB
$57-300/month (Atlas M10-M30)
PostgreSQL
$15-100/month (RDS/Managed)(winner)
Full Comparison
| Attribute | MongoDB | PostgreSQL |
|---|---|---|
| Transaction Support(consistency level) | Multi-document ACID (since v4.0, snapshot isolation) | — |
| Index Types Supported(count) | 10+ (single field, compound, geospatial, text, wildcard) | 20+ (B-tree, hash, BRIN, GiST, partial indexes)(winner) |
| Query Language Standard | MongoDB Query Language (MQL) | — |
| Built-in Authentication | No (third-party only) | — |
| Schema Flexibility | Schema-less (dynamic fields) | Fixed schema (requires ALTER) |
Show 15 more attributesAuto-generated API Manual API layer required — Query Language Complexity Support(capability level) Aggregation pipeline (moderate for complex queries) Full SQL with unlimited JOIN depth and CTEs Query Language Complexity MQL (simpler for simple queries, steeper for complex joins) SQL (steep initial curve, powerful at scale) Extension Ecosystem(available extensions) Limited (core features only) 75+ community extensions JSON Query Capability JSONB with full indexing — Full-Text Search Comprehensive native support — Time-Series Optimization TimescaleDB extension native — Built-in Authentication Methods(methods) 0 (requires third-party) — Real-time Subscriptions Support(native support) Not native - requires extensions — Database Branching Capability Not built-in — Auto-Scaling Support Manual or third-party tools required — Full-Text Search Languages Supported(languages) 15+ languages — Built-in JSON Support Yes, comprehensive with operators and indexing — Full-Text Search Capability Native with ranking, stemming, 15+ languages — Window Functions Support Full support with 20+ window functions — | ||
| Horizontal Scalability | Native automatic sharding across nodes | Manual sharding required |
| Horizontal Scaling Method | Manual sharding + Atlas auto-scaling | — |
| Average Query Latency (structured data)(ms) | 8-12ms for equivalent queries | — |
| Write Throughput (single server)(operations/second) | 100,000-500,000 ops/sec | — |
| Write Throughput (bulk inserts)(documents/second) | 50,000-100,000 docs/sec(winner) | 15,000-25,000 docs/sec |
| Memory Usage (100K documents)(MB) | 250-350 MB | 150-200 MB(winner) |
| Baseline Latency(milliseconds) | 5-10ms (cluster dependent) | — |
Show 20 more attributesRead Throughput (1TB dataset)(ops/second) 10,000-50,000 ops/sec — Maximum Concurrent Connections(connections) Unlimited (scales with cluster) 1,000+ Real-time Capabilities(ms latency) Change Streams (enterprise feature) — Average Query Latency(milliseconds) 10-50 ms — Query Response Time (Median)(ms) 38 ms (indexed query) — Max Write Throughput (Optimized)(writes/second) ~50,000 (sharded cluster) ~10,000 (single node) Storage Efficiency(% overhead) 25-40% (document format, field duplication) 5-15% (optimized row format) Join Performance on 1M+ rows(seconds) 8-15+ seconds ($lookup) 0.5-2 seconds (optimized joins) Simple Query Throughput(queries/sec) ~25,000 (PostgreSQL 18) — Complex Join Performance(ms response time) ~320 (5-table join) — Replication Lag (typical)(ms) 10-100 (WAL) — Single-Node Write Throughput(writes/sec) 35,000 writes/sec — Maximum Database Size(items supported) Unlimited (petabyte+ capable) — Simple SELECT Query Speed(milliseconds (relative)) 115-120ms — Auto-scaling Response Time(seconds) Manual; requires 5-60 minutes intervention — Cold Start Latency(milliseconds) 0 seconds (always running) — Complex Analytical Query Speed (with JOINs + aggregations)(milliseconds (relative)) 320ms (with window functions) — Simple Query Speed (1M rows, SELECT *)(milliseconds) 52ms (PostgreSQL) — Complex Analytical Query Speed (Aggregate + Join)(milliseconds) 850ms (PostgreSQL) — Minimum Memory Requirement(MB) 100MB — | ||
| Memory Usage (100GB dataset)(GB) | 24-36GB working set | — |
| Years in Production(years) | 19 years (MongoDB 1.0 released 2009) | — |
| Production Maturity (Years Active)(years) | 25+ years | — |
| Community Popularity(% of developers) | 28% of web applications (Stack Overflow 2024) | — |
| Developer Preference (2024 Survey)(%) | 44% | — |
| Multi-row/Document Transactions(null) | ACID from v4.0 (slower than PostgreSQL) | Full multi-statement ACID |
| ACID Compliance Scope | Multi-document transactions (4.0+) | Full transaction coverage (all operations) |
| ACID Compliance Level | Complete (all operations) | — |
| Automatic Daily Backups(boolean) | Not included - manual setup required | — |
| Query Language Complexity (learning curve)(months) | 2-4 weeks (MongoDB Query Language simpler syntax) | 1-2 months (SQL standardized, widely taught)(winner) |
| Enterprise Support(SLA hours) | MongoDB Atlas managed cloud (SaaS); community edition free | Free open-source; commercial support available |
| Enterprise Support Availability | EDB, multiple vendors | — |
| Free Tier Storage(GB) | 0 GB (Atlas free tier discontinued) | — |
| Minimum Monthly Cost (Production)(USD) | $57 (M10 Atlas cluster) | $20-50 (cloud VM minimum)(winner) |
| Minimum Monthly Cost (Managed)(USD) | $57 | — |
| Startup Monthly Cost(USD) | $57/month | — |
| Free Tier Database Storage(GB) | 512 MB | — |
Show 5 more attributesSelf-Hosted Cost (Base)(USD/month) $0 (open-source) — Monthly Base Cost (Small Instance)(USD) $0 (infrastructure cost only) — Minimum Monthly Cost(USD) $0 (open-source) — Production Tier Monthly Base Cost(USD) $0 (self-hosted only) — Monthly Cost (100 GB, moderate traffic)(USD) $50-200+ (self-hosted infrastructure) or $100-500 (managed provider) — | ||
| Minimum Production Tier Cost(USD/month) | $57 | — |
| Transaction ACID Support | Multi-document (v4.0+) | — |
| Foreign Key Support | Not enforced natively | — |
| ACID Compliance by Default | Yes (default) | — |
| Maximum Connections Per Database(connections) | Unlimited (sharding dependent) | — |
| Annual npm Downloads (Drivers)(millions) | 21.7M | — |
| Query Complexity Support | 200+ query operators, joins, aggregation pipeline | — |
| Transaction Scope | Multi-document ACID across collections | — |
| Horizontal Scaling | Manual sharding configuration required | — |
| Max Horizontal Scalability | Unlimited (sharding across clusters) | — |
| Native Horizontal Scaling | Yes (automatic sharding) | No (requires partitioning/third-party) |
| Sharding (Horizontal Scaling) | Native, automatic shard distribution | Requires external tools (Citus, pg_partman) |
| Maximum Connections(concurrent connections) | Unlimited (hardware-dependent) | — |
Show 1 more attributeMaximum Connection Limit (Default)(connections) 100 — | ||
| Operational Complexity(level) | Moderate to high (backups, sharding, monitoring) | — |
| Time to Production Deployment(minutes) | 40-80 hours | — |
| Setup DevOps Requirement(hours/month) | 20-40 hours | — |
| Document Size Limit(MB) | 16 MB | — |
| Query Complexity (Aggregation Capability)(rating 1-10) | 9 (full aggregation pipeline) | — |
| Read Operations (Free Tier Monthly)(operations) | No free tier | — |
| Real-time Sync Implementation Effort(days) | 5-10 days (custom code) | — |
| Required DevOps Knowledge | High (infrastructure management needed) | — |
| Setup Time (Fresh Installation)(minutes) | 30-60 minutes | — |
| Monthly Cost (Entry Paid Tier)(USD) | $57 | — |
| Maximum Database Size (Free Tier)(GB) | 0.512 GB | — |
| ACID Transaction Support(boolean) | Multi-document (v4.0+, with limitations) | Full compliance, all operations |
| Storage Overhead (vs Equivalent Relational)(multiple) | 2-3x larger (denormalization) | 1x baseline (normalized)(winner) |
| Schema Enforcement | Optional/flexible (schema-on-read) | Required (schema-on-write) |
| Community Size & Ecosystem(relative rank) | ~25k stars(winner) | ~15k stars |
| Typical Setup Complexity(time to production (hours)) | 4-8 hours (managed cloud option available) | 2-4 hours (widely supported, simpler setup)(winner) |
| Starting Managed Hosting Cost(USD/month) | $57 (Atlas M10) | $15 (RDS free tier + $20)(winner) |
| AWS RDS Managed Cost($/month (db.t3.micro, single-AZ)) | $15.25 (PostgreSQL 18) | — |
| License Cost (Annual, Small Enterprise)(USD) | $0 | — |
| Base Memory Footprint(MB) | ~150 (minimal config) | — |
| Default Memory Usage(MB) | 300MB | — |
| Vector Similarity Support | Native pgvector | — |
| Supported Versions (2026)(major versions) | 5 (14-18 active) | — |
| Minimum Cluster Size(nodes) | 1 (single instance) | — |
| Supported Geographic Regions(count) | Unlimited (self-hosted) | — |
| Multi-Region Failover Time (RTO)(seconds) | Manual, typically 5-15 minutes | — |
| PostgreSQL SQL Compatibility(percent) | 100% (native) | — |
| GitHub Stars(stars) | 3,500+ stars | — |
| Time to Production(days) | 120-1440 minutes (self-hosted) | — |
| Hosting Provider Compatibility(percent) | 85% of providers | — |
| Vendor Lock-in Risk(risk level) | Zero - 100% portable SQL | — |
| Supported Concurrent Connections (Free Tier)(connections) | Unlimited (depends on installation) | — |
| Maximum Storage (Base Plan)(GB) | Unlimited (hardware dependent) | — |
| Time to Deploy Production Database(minutes) | 240-1440 minutes (4-24 hours) | — |
| Point-in-Time Recovery Retention(days) | Customizable via WAL archiving | — |
| Data Portability(score out of 10) | Trivial (native format, zero lock-in) | — |
| Available PostgreSQL Extensions(count) | 500+ (all available from PostgreSQL ecosystem) | — |
| Community Size & Support(user base estimate) | 10,000,000+ deployments globally | — |
| Maximum JSON Document Size(GB) | 1GB+ (JSONB) | — |
| Window Functions Availability | Yes (since 8.4) | — |
MMongoDB
PostgreSQLTransaction Support(consistency level)
Multi-document ACID (since v4.0, snapshot isolation)
—
Index Types Supported(count)
10+ (single field, compound, geospatial, text, wildcard)
20+ (B-tree, hash, BRIN, GiST, partial indexes)
Query Language Standard
MongoDB Query Language (MQL)
—
Built-in Authentication
No (third-party only)
—
Schema Flexibility
Schema-less (dynamic fields)
Fixed schema (requires ALTER)
Show 15 more attributes
Auto-generated API
Manual API layer required
—
Query Language Complexity Support(capability level)
Aggregation pipeline (moderate for complex queries)
Full SQL with unlimited JOIN depth and CTEs
Query Language Complexity
MQL (simpler for simple queries, steeper for complex joins)
SQL (steep initial curve, powerful at scale)
Extension Ecosystem(available extensions)
Limited (core features only)
75+ community extensions
JSON Query Capability
JSONB with full indexing
—
Full-Text Search
Comprehensive native support
—
Time-Series Optimization
TimescaleDB extension native
—
Built-in Authentication Methods(methods)
0 (requires third-party)
—
Real-time Subscriptions Support(native support)
Not native - requires extensions
—
Database Branching Capability
Not built-in
—
Auto-Scaling Support
Manual or third-party tools required
—
Full-Text Search Languages Supported(languages)
15+ languages
—
Built-in JSON Support
Yes, comprehensive with operators and indexing
—
Full-Text Search Capability
Native with ranking, stemming, 15+ languages
—
Window Functions Support
Full support with 20+ window functions
—
Horizontal Scalability
Native automatic sharding across nodes
Manual sharding required
Horizontal Scaling Method
Manual sharding + Atlas auto-scaling
—
Average Query Latency (structured data)(ms)
8-12ms for equivalent queries
—
Write Throughput (single server)(operations/second)
100,000-500,000 ops/sec
—
Write Throughput (bulk inserts)(documents/second)
50,000-100,000 docs/sec
15,000-25,000 docs/sec
Memory Usage (100K documents)(MB)
250-350 MB
150-200 MB
Baseline Latency(milliseconds)
5-10ms (cluster dependent)
—
Show 20 more attributes
Read Throughput (1TB dataset)(ops/second)
10,000-50,000 ops/sec
—
Maximum Concurrent Connections(connections)
Unlimited (scales with cluster)
1,000+
Real-time Capabilities(ms latency)
Change Streams (enterprise feature)
—
Average Query Latency(milliseconds)
10-50 ms
—
Query Response Time (Median)(ms)
38 ms (indexed query)
—
Max Write Throughput (Optimized)(writes/second)
~50,000 (sharded cluster)
~10,000 (single node)
Storage Efficiency(% overhead)
25-40% (document format, field duplication)
5-15% (optimized row format)
Join Performance on 1M+ rows(seconds)
8-15+ seconds ($lookup)
0.5-2 seconds (optimized joins)
Simple Query Throughput(queries/sec)
~25,000 (PostgreSQL 18)
—
Complex Join Performance(ms response time)
~320 (5-table join)
—
Replication Lag (typical)(ms)
10-100 (WAL)
—
Single-Node Write Throughput(writes/sec)
35,000 writes/sec
—
Maximum Database Size(items supported)
Unlimited (petabyte+ capable)
—
Simple SELECT Query Speed(milliseconds (relative))
115-120ms
—
Auto-scaling Response Time(seconds)
Manual; requires 5-60 minutes intervention
—
Cold Start Latency(milliseconds)
0 seconds (always running)
—
Complex Analytical Query Speed (with JOINs + aggregations)(milliseconds (relative))
320ms (with window functions)
—
Simple Query Speed (1M rows, SELECT *)(milliseconds)
52ms (PostgreSQL)
—
Complex Analytical Query Speed (Aggregate + Join)(milliseconds)
850ms (PostgreSQL)
—
Minimum Memory Requirement(MB)
100MB
—
Memory Usage (100GB dataset)(GB)
24-36GB working set
—
Years in Production(years)
19 years (MongoDB 1.0 released 2009)
—
Production Maturity (Years Active)(years)
25+ years
—
Community Popularity(% of developers)
28% of web applications (Stack Overflow 2024)
—
Developer Preference (2024 Survey)(%)
44%
—
Multi-row/Document Transactions(null)
ACID from v4.0 (slower than PostgreSQL)
Full multi-statement ACID
ACID Compliance Scope
Multi-document transactions (4.0+)
Full transaction coverage (all operations)
ACID Compliance Level
Complete (all operations)
—
Automatic Daily Backups(boolean)
Not included - manual setup required
—
Query Language Complexity (learning curve)(months)
2-4 weeks (MongoDB Query Language simpler syntax)
1-2 months (SQL standardized, widely taught)
Enterprise Support(SLA hours)
MongoDB Atlas managed cloud (SaaS); community edition free
Free open-source; commercial support available
Enterprise Support Availability
EDB, multiple vendors
—
Free Tier Storage(GB)
0 GB (Atlas free tier discontinued)
—
Minimum Monthly Cost (Production)(USD)
$57 (M10 Atlas cluster)
$20-50 (cloud VM minimum)
Minimum Monthly Cost (Managed)(USD)
$57
—
Startup Monthly Cost(USD)
$57/month
—
Free Tier Database Storage(GB)
512 MB
—
Show 5 more attributes
Self-Hosted Cost (Base)(USD/month)
$0 (open-source)
—
Monthly Base Cost (Small Instance)(USD)
$0 (infrastructure cost only)
—
Minimum Monthly Cost(USD)
$0 (open-source)
—
Production Tier Monthly Base Cost(USD)
$0 (self-hosted only)
—
Monthly Cost (100 GB, moderate traffic)(USD)
$50-200+ (self-hosted infrastructure) or $100-500 (managed provider)
—
Minimum Production Tier Cost(USD/month)
$57
—
Transaction ACID Support
Multi-document (v4.0+)
—
Foreign Key Support
Not enforced natively
—
ACID Compliance by Default
Yes (default)
—
Maximum Connections Per Database(connections)
Unlimited (sharding dependent)
—
Annual npm Downloads (Drivers)(millions)
21.7M
—
Query Complexity Support
200+ query operators, joins, aggregation pipeline
—
Transaction Scope
Multi-document ACID across collections
—
Horizontal Scaling
Manual sharding configuration required
—
Max Horizontal Scalability
Unlimited (sharding across clusters)
—
Native Horizontal Scaling
Yes (automatic sharding)
No (requires partitioning/third-party)
Sharding (Horizontal Scaling)
Native, automatic shard distribution
Requires external tools (Citus, pg_partman)
Maximum Connections(concurrent connections)
Unlimited (hardware-dependent)
—
Show 1 more attribute
Maximum Connection Limit (Default)(connections)
100
—
Operational Complexity(level)
Moderate to high (backups, sharding, monitoring)
—
Time to Production Deployment(minutes)
40-80 hours
—
Setup DevOps Requirement(hours/month)
20-40 hours
—
Document Size Limit(MB)
16 MB
—
Query Complexity (Aggregation Capability)(rating 1-10)
9 (full aggregation pipeline)
—
Read Operations (Free Tier Monthly)(operations)
No free tier
—
Real-time Sync Implementation Effort(days)
5-10 days (custom code)
—
Required DevOps Knowledge
High (infrastructure management needed)
—
Setup Time (Fresh Installation)(minutes)
30-60 minutes
—
Monthly Cost (Entry Paid Tier)(USD)
$57
—
Maximum Database Size (Free Tier)(GB)
0.512 GB
—
ACID Transaction Support(boolean)
Multi-document (v4.0+, with limitations)
Full compliance, all operations
Storage Overhead (vs Equivalent Relational)(multiple)
2-3x larger (denormalization)
1x baseline (normalized)
Schema Enforcement
Optional/flexible (schema-on-read)
Required (schema-on-write)
Community Size & Ecosystem(relative rank)
~25k stars
~15k stars
Typical Setup Complexity(time to production (hours))
4-8 hours (managed cloud option available)
2-4 hours (widely supported, simpler setup)
Starting Managed Hosting Cost(USD/month)
$57 (Atlas M10)
$15 (RDS free tier + $20)
AWS RDS Managed Cost($/month (db.t3.micro, single-AZ))
$15.25 (PostgreSQL 18)
—
License Cost (Annual, Small Enterprise)(USD)
$0
—
Base Memory Footprint(MB)
~150 (minimal config)
—
Default Memory Usage(MB)
300MB
—
Vector Similarity Support
Native pgvector
—
Supported Versions (2026)(major versions)
5 (14-18 active)
—
Minimum Cluster Size(nodes)
1 (single instance)
—
Supported Geographic Regions(count)
Unlimited (self-hosted)
—
Multi-Region Failover Time (RTO)(seconds)
Manual, typically 5-15 minutes
—
PostgreSQL SQL Compatibility(percent)
100% (native)
—
GitHub Stars(stars)
3,500+ stars
—
Time to Production(days)
120-1440 minutes (self-hosted)
—
Hosting Provider Compatibility(percent)
85% of providers
—
Vendor Lock-in Risk(risk level)
Zero - 100% portable SQL
—
Supported Concurrent Connections (Free Tier)(connections)
Unlimited (depends on installation)
—
Maximum Storage (Base Plan)(GB)
Unlimited (hardware dependent)
—
Time to Deploy Production Database(minutes)
240-1440 minutes (4-24 hours)
—
Point-in-Time Recovery Retention(days)
Customizable via WAL archiving
—
Data Portability(score out of 10)
Trivial (native format, zero lock-in)
—
Available PostgreSQL Extensions(count)
500+ (all available from PostgreSQL ecosystem)
—
Community Size & Support(user base estimate)
10,000,000+ deployments globally
—
Maximum JSON Document Size(GB)
1GB+ (JSONB)
—
Window Functions Availability
Yes (since 8.4)
—
Pros & Cons
10 pros·6 cons across both
M
M
MongoDB
+5-3
Pros
- Native sharding for horizontal scaling across distributed clusters
- Schema-less design allows rapid iteration without migrations
- Multi-document ACID transactions (MongoDB 4.0+) for complex operations
- Excellent for nested/hierarchical data (embedded documents reduce joins)
- Strong community (4.2M+ downloads/month on npm)
Cons
- Higher storage overhead due to document format and field duplication across shards
- Significantly more expensive (2-3x) than comparable PostgreSQL managed services
- Join operations ($lookup) perform poorly on large datasets compared to SQL
PostgreSQL
+5-3
Pros
- Full ACID compliance across all transactions and operations
- Powerful SQL with window functions, CTEs, and complex joins
- Lower operational costs and hosting fees ($15-100/month vs $57-300)
- Excellent for structured data with strong data integrity requirements
- Rich ecosystem with 75+ extension types (PostGIS, TimescaleDB, pgvector)
Cons
- Horizontal scaling requires external tools (Citus, Patroni) increasing complexity
- Fixed schema requires migrations for structural changes
- Less ideal for highly nested/unstructured data requiring denormalization
Frequently Asked Questions
5 questions
It depends on the use case. MongoDB excels at write-heavy, unstructured workloads and can be 30-50% faster for simple document retrieval. PostgreSQL is 5-15x faster for complex queries with multiple joins. For your specific scenario, benchmark both with your actual query patterns.
Resources & Learn More
Curated sources to dive deeper
Where to Buy
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Wikipedia
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