Document Retrieval Systems
Specialized systems for storing, indexing, and retrieving documents and their metadata.
Supported Solution Fields
When to Use
- When you need document-centric search
- When metadata management is important
- When you need version control
- When you need document processing pipelines
When Not to Use
- When you only need simple file storage
- When real-time search isn't required
- When you don't need document processing
- When you need general-purpose search
Tradeoffs
- Features vs Complexity: More features mean more complex setup
- Processing vs Speed: Better processing means slower indexing
- Storage vs Access: Better access requires more storage
- Managed vs Self-hosted: Ease of use versus control
Commercial Implementations
-
OpenSearch
- Open source
- Document-focused
- Good scalability
- AWS integration
-
MongoDB Atlas Search
- Integrated search
- Document-native
- Good performance
- Atlas platform
-
Azure Cognitive Search
- AI-enriched search
- Document cracking
- Managed service
- Enterprise focus
Common Combinations
- Content management
- Digital libraries
- Legal document systems
- Research repositories
- Enterprise archives
Case Study: Legal Document Management
A law firm implemented document retrieval for their case files:
Challenge
- Complex document types
- Strict security needs
- Fast retrieval required
- Version tracking needed
Solution
- Implemented OpenSearch
- Custom security plugins
- Automated metadata extraction
- Version control integration
Results
- 70% faster document retrieval
- Improved security compliance
- Better document organization
- Reduced manual filing work