mongoexport: AI-Optimized Technical Reference

Overview

MongoDB tool for exporting collection data to JSON/CSV format. Version 100.13.0 (August 2025). Single-threaded, memory-intensive tool with significant limitations on large datasets.

Core Functionality

Primary Capabilities

• JSON Export: Preserves document structure with nested objects/arrays
• CSV Export: Flattens data structure (causes data corruption for complex documents)
• Query Filtering: Supports MongoDB query syntax with --query parameter
• Authentication: Full MongoDB auth method support including Atlas connections

Critical Limitations

• Single Collection Only: Cannot export multiple collections simultaneously
• No Resume Capability: Failed exports must restart from beginning
• Single-Threaded: Uses only one CPU core regardless of system capacity
• Not for Backups: Destroys BSON type information (dates become strings, NumberLongs become regular numbers)

Performance Characteristics

Memory Usage Patterns

• Failure Threshold: Collections >10M documents cause OOM kills
• Memory Consumption: Loads significantly more data than collection size on disk
• Observed Behavior: 2GB collection can consume >16GB RAM
• Error Pattern: mongoexport: killed (signal 9) from OOM killer

Speed Performance

• Large Collections: 18 hours for operations that should take 30 minutes
• Progress Rate: 0.1% progress after 6 hours on large datasets
• CPU Utilization: Single core at 100%, remaining cores idle
• Comparative Speed: Significantly slower than mongodump

Scalability Workarounds

• Pagination Required: Use --skip and --limit for collections >1M documents
• Chunk Size: 100k documents per chunk to avoid memory issues
• Manual Scripting: Required for bulk operations

Production Configuration

Installation Methods

• Package Managers: Unreliable, often installs outdated versions
• Direct Download: Recommended approach from MongoDB Database Tools package
• Docker: Available but complicates connection debugging
• Dependency Issues: Common on Linux distributions

Connection Settings

• Sharded Clusters: Use --readPreference=secondary to avoid primary load
• Timeout Issues: Expect random disconnections on large exports
• Authentication: Use config files to avoid password exposure in shell history
• Config File: --config=/path/to/config.yaml with chmod 600 permissions

Production Commands

Basic Export (Small Collections Only)

mongoexport --collection=events --db=reporting --out=events.json

CSV Export with Field Selection

mongoexport --db=users --collection=contacts --type=csv --fields=name,email,created_at --out=contacts.csv

Filtered Export with Date Range

mongoexport --db=sales --collection=orders --query='{"status": "completed", "created": {"$gte": {"$date": "2025-01-01T00:00:00Z"}}}' --out=completed_orders.json

Chunked Export for Large Collections

mongoexport --skip=0 --limit=100000 --db=big --collection=data --out=data_1.json
mongoexport --skip=100000 --limit=100000 --db=big --collection=data --out=data_2.json

Tool Comparison Matrix

Tool	Speed	Memory Usage	Data Integrity	Cost	Use Case
mongoexport	Very Slow	Excessive	Destroys types	Free	Small data analysis
mongodump	Fast	Reasonable	Preserves all	Free	Backups
Studio 3T	Moderate	Moderate	Variable	$199+/year	Rich analysis
Compass	Very Slow	Reasonable	Destroys types	Free	GUI exports

Failure Scenarios

Memory Exhaustion

• Trigger: Collections >10M documents or complex nested structures
• Symptom: Killed (signal 9) error message
• Impact: Complete export failure, no partial recovery
• Mitigation: Implement chunking strategy with skip/limit

Connection Timeouts

• Trigger: Large exports on sharded clusters
• Symptom: network error while attempting to run command 'getMore'
• Impact: Export failure after hours of processing
• Mitigation: Use secondary read preference, implement retry logic

CSV Data Corruption

• Trigger: Nested objects or arrays in documents
• Symptom: JSON strings within CSV fields, unusable data structure
• Impact: Requires manual post-processing or format change
• Mitigation: Use JSON format for complex documents

Decision Criteria

Use mongoexport When

• Collection size <1M documents
• Simple document structure
• Need human-readable format
• Integration with external JSON/CSV consumers

Avoid mongoexport When

• Creating backups (use mongodump)
• Collections >10M documents
• Performance is critical
• Need to export multiple collections
• Complex nested document structures

Resource Requirements

Time Investment

• Small Collections (<100k docs): Minutes
• Medium Collections (1M docs): Hours with chunking
• Large Collections (>10M docs): Days with manual scripting

Expertise Requirements

• Basic: MongoDB query syntax knowledge
• Intermediate: Shell scripting for chunking large exports
• Advanced: Memory management and connection troubleshooting

System Resources

• Minimum RAM: 4GB for small collections
• Recommended RAM: 16GB+ for medium collections
• CPU: Single-core utilization regardless of available cores
• Disk Space: 2-3x collection size for JSON exports

Critical Warnings

Official Documentation Gaps

• Memory usage patterns not documented
• Performance characteristics not quantified
• No guidance for large collection handling
• Missing production deployment considerations

Breaking Points

• 10M documents: Memory exhaustion threshold
• Complex nesting: CSV format becomes unusable
• Sharded clusters: Connection stability issues
• Long-running exports: No progress recovery mechanism

Hidden Costs

• Human time: Manual chunking and monitoring required
• Infrastructure: Higher memory requirements than documented
• Operational complexity: Scripting required for production use
• Data integrity: Type information loss requires validation