Document Database

A Document Database is a document-structured semi-structured database instance that contains document records.

• AKA: Document-Oriented Database, Document Store, Document Dataset, Document-Based Database, Document Collection Database.
• Context:
  • It can typically contain Document Records with nested fields and hierarchical structures.
  • It can typically store JSON Documents, BSON Documents, or XML Documents as primary data elements.
  • It can typically support Document Querys through field selectors and nested path expressions.
  • It can typically maintain Document Collections that group related documents together.
  • It can typically provide Document Indexes for query optimization and search performance.
  • ...
  • It can often include Document Metadata such as creation timestamps and revision numbers.
  • It can often support Document Relationships through document references and embedded documents.
  • It can often enable Document Aggregation through pipeline operations and map-reduce functions.
  • It can often maintain Document Consistency through transaction boundarys and isolation levels.
  • ...
  • It can range from being a Small Document Database to being a Large Document Database, depending on its document count.
  • It can range from being a Single-Collection Document Database to being a Multi-Collection Document Database, depending on its collection structure.
  • It can range from being a Flat Document Database to being a Deeply-Nested Document Database, depending on its document complexity.
  • It can range from being a Read-Heavy Document Database to being a Write-Heavy Document Database, depending on its operation pattern.
  • It can range from being a Static Document Database to being a Dynamic Document Database, depending on its update frequency.
  • It can range from being a Homogeneous Document Database to being a Heterogeneous Document Database, depending on its schema variation.
  • ...
  • It can be created by a Document-Oriented Database Platform through database creation operations.
  • It can be managed by a Database Administrator through administrative interfaces and management tools.
  • It can be accessed by a Database Application through database drivers and connection protocols.
  • It can be backed up through a Database Backup Process using backup utilitys and recovery procedures.
  • ...
• Example(s):
  • E-Commerce Document Databases, such as:
    • Amazon Product Catalog Database containing product documents with price, description, and inventory data.
    • eBay Listing Database containing auction documents with bid history and seller information.
    • Shopify Store Database containing merchant products and order documents.
  • Content Management Document Databases, such as:
    • Wikipedia Article Database containing encyclopedia articles with revision history.
    • Medium Publication Database containing blog post documents with author metadata.
    • BBC News Database containing news article documents with multimedia content.
  • User Profile Document Databases, such as:
    • Facebook User Database containing user profile documents with social connections.
    • LinkedIn Member Database containing professional profile documents with career history.
    • Twitter Account Database containing user documents with tweet collections.
  • Healthcare Document Databases, such as:
    • Epic EHR Database containing patient record documents with medical history.
    • Mayo Clinic Patient Database containing clinical documents with treatment plans.
    • NHS Patient Record Database containing health record documents with prescription data.
  • Financial Document Databases, such as:
    • JPMorgan Transaction Database containing transaction documents with payment details.
    • Visa Payment Database containing payment documents with merchant information.
    • Bloomberg Market Database containing financial instrument documents with market data.
  • ...
• Counter-Example(s):
  • Relational Database, which stores table rows rather than document records.
  • Key-Value Database, which stores key-value pairs without document structure.
  • Graph Database, which stores graph nodes and graph edges.
  • Document Corpus, which is a research collection rather than an operational database.
  • File System Directory, which stores files without database capability.
• See: Database Instance, Semi-Structured Database, NoSQL Database, Document-Oriented Database Platform, Document Record, JSON Document, Database Collection, Document Query Language, MongoDB Database System.

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