The Stardog Blog
Get the latest in your inbox
Get the latest in your inbox
Stardog recently released a Knowledge Catalog as part of its knowledge graph platform, which easily extends to quickly harvest enterprise metadata with integrations for Databricks Unity, Collibra and Microsoft Purview Data catalogs, and any JDBC-accessible data source.
This blog post will show you how easy it is to get started with knowledge graphs using Stardog Cloud.
As you might have heard, Stardog is applying Large Language Models (LLMs) to enterprise knowledge graph technology. So what does this actually mean?
In this article, you’ll understand the three types of Knowledge Kits offered by Stardog, their use cases, and how to access them. Spoiler alert: they are all free.
We’re at the beginning of a revolution in machine-understandable semantics powered by Large Language Model breakthroughs. Stardog Voicebox, powered by LLMs, will fundamentally flatten the enterprise knowledge graph (EKG) implementation cost curve.
The “metrics layer” is the oldest and foundational semantic layer use case. But there’s a new breed of semantic layer use cases that Stardog and its customers are pioneering.
Data mesh is a new way of thinking about data based on a distributed architecture for data management. Learn more about what it is and how to use it.
Are you managing data and analytics at your organization? Learn how tech leaders are using knowledge graphs to transform their approach.
The secret to data analytics success today is a democratized, self-service data platform, and that’s only possible when you leverage a semantic layer to shift from columns to concepts.
Modern enterprises need to develop a Data Governance Framework. For effective governance, this is generally underpinned by a catalog megastore. Unity Catalog provides that megastore across the lakehouse, enabling business users access to full metadata across the workspaces and allowing them to visualize the relationships across the data landscape. The creation of a knowledge layer is accelerated when this metadata is available for modeling in Stardog platform.
How do companies use graph databases in real life? At Stardog, our platform combines graph technology with semantics to enable knowledge graphs. Consider the ability to deeply understand and work with connections between organizations, people, transactions, and events (to name a few examples). Add in inferencing, scalability, and near real-time traversal of big data. The number of graph use cases explodes. Relational databases like SQL simply can’t deliver like graph can.
There are many reasons for data and analytics leaders to embrace graph techniques. These techniques can provide unique insight into business problems, especially those problems requiring contextual awareness of the connections and disconnections between multiple entities, including organizations, people, transactions, and events. A well-designed and richly populated graph can capture essential data relationships and their variable nature.