Graph-Based Data Storage for Multi-Domain Retrieval
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Solution Overview
Problem
Existing database systems face challenges in efficiently storing and retrieving large numbers of documents across multiple domains, leading to redundant data stores, duplication of maintenance efforts, and scalability issues, particularly in social networking applications that need to combine data from different domains.
Innovation Solution
The Every Document as a Graph (EVG) system uses a graph-based model to abstract data sources, allowing for efficient storage and retrieval of metadata-driven data from multiple domains, enabling scalable operations and reducing duplicate efforts by representing every document and relationship as a graph, with a shared, multi-tenant service that acts as a proxy to various data store implementations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored in a single database in a single domain, then data storage and retrieval is simple, but scalability and ability to handle multi-domain data are limited
Solution Approach 1:
The patent segments data into distinct domains (e.g., social network data, email data, calendar data) while maintaining a unified database structure. Each domain can be independently managed and queried, allowing the system to handle multi-domain data without requiring a completely new system for each domain.
Solution Approach 2:
The patent creates a universal database system that can handle multiple types of data (social networks, emails, calendars, documents) within a single database. The system provides domain-specific query languages and abstractions for each data type while maintaining a common storage and management infrastructure, enabling one system to serve multiple functions.
2Ease of manufacture
If multiple data stores are used for different domains, then data organization is improved, but redundant data stores and duplication of maintenance effort increase
Solution Approach 1:
The patent merges multiple domain-specific data stores into a single unified database system. While maintaining logical separation of different data types through domain-specific schemas and query languages, the physical infrastructure, maintenance operations, and management functions are consolidated into one system, eliminating redundant maintenance efforts.
Solution Approach 2:
The patent introduces domain-specific query languages and abstractions as intermediaries between the user and the unified database. These intermediaries provide domain-specific data organization and access patterns while translating queries into efficient operations on the underlying unified storage system, maintaining ease of data organization without requiring separate physical data stores.
3Speed
If traditional database systems are used, then implementation is straightforward, but retrieval speed and efficiency for complex queries deteriorate
Solution Approach 1:
The patent optimizes the database system for different query types by implementing domain-specific query languages and access patterns tailored to each data type (social networks, emails, calendars). Each domain has optimized retrieval paths and data structures suited to its specific query patterns, improving retrieval speed without requiring a completely different system for each domain.
Solution Approach 2:
The patent changes the parameters of the database system by introducing domain-specific schemas, data models, and query optimization strategies for different data types. By adjusting these parameters rather than changing the fundamental database architecture, the system achieves faster retrieval speeds for complex queries while maintaining implementation feasibility.
Data Source
AI summary
Structure of a resultant Every Document as a Graph (EVG) graph may be outlined using an EVG query. First metadata for a first data source may be retrieved. At least one entity key may be determined for a first entity, the entity key coming directly from the EVG query or from an entity on a preceding level of the EVG graph. Based on the first metadata and entity key, an edge may be created in the EVG graph beginning at the first entity, wherein the edge contains information retrieved from the first data source. Second metadata for a second data source may be retrieved. Based on the second metadata and information contained in the edge retrieved from first data source, a second entity may be created in the EVG graph, wherein the edge connects to the second entity, wherein the second entity contains information retrieved from the second data source.