Big Data vs Small Data

Entity-centric describes the organizational structure of the patent-pending shared database of the Dataparency Platform.

All data in the platform is stored by entity descriptor as a hierarchical 'document'. This structure allows any data of a particular entity to be retrieved in one operation without the multiple table joins required by a RDBMS. This improves efficiency of operation while simplifying development. No complicated foreign key designs to fail when schemas change as they always do.

For queries of the big data of the platform, multiple data servers accomplish this in a paralleled, map/reduce fashion, for near realtime analytics. Queries are broadcast to all servers (map) and results are combined (reduce) to return the results.

Resource-oriented describes the method by which data is retrieved/stored in the platform database.

Data in the hierarchical 'document' of the platform is organized as aspects of the entity. These aspects describe groupings of like data such as demographics, features, events, etc. They are accessed by a RESTful API, using HTTPS GET/POST, passing a resource URI: indicating the entity and the aspect and qualifiers for the data desired.

GraphQL (optional module) provides a simplified interface to the database. It allows syntax and semantic structuring of data access/update and provides ALL the data you require in a single server request. No multiple, time-consuming, requests to gather all the data your interface needs.