Artificial Intelligence Improves when Graph and Document Databases Become One
Franz’s CEO, Jans Aasman’s recent AI Time Journal article:
As companies realize the promise of Artificial Intelligence often includes the challenge of integrating highly diverse, increasing complex data sources, the value of semantic graph databases has strengthened tremendously in recent years. Semantic graphs not only enable organizations to seamlessly align unstructured data with semi-structured and structured data—effectively making all data manageable as though structured, but also facilitate interoperability across databases, IT systems, and locations via universal standards.
But these benefits become even more extensible when equipped with the core capabilities of document stores. By augmenting the underlying graph technology with native support for JSON and JSON-LD, organizations can suddenly access a range of possibilities for AI data modeling, querying and developing applications previously impossible.
The heightened utility of a hybrid graph/document store allows organizations to link and access numerous documents, comma separated value (CSV) files, and structured data with a single query, as well as leverage the modeling and formatting flexibility of document stores within the context of their overall data assets. The result is a richer dataset for artificial intelligence, analytics, application development and web services, making data themselves inherently more valuable.
Read the full article at AI Time Journal