Data Integration

Data fabric is the future of data management

Seamlessly upgrade to a data fabric

What is data integration?

Data integration platforms are designed to combine data sources that were originally created separately so that they can be used together.

The limitations of traditional data integration

Most data integration systems are supported by relational data frameworks, i.e. the tabular systems you likely are familiar with from everyday use. Relational data frameworks are ideal for stable business processes where you are dealing with unchanging reporting requirements. But what works for your data warehouse doesn’t necessarily work for large-scale integration. Today, data and analytics leaders need to quickly support iterative question and answer cycles from the business and easily uncover new insight from their data. Data management practices must be able to support unanticipated questions to quickly deliver insight to the business.

Data integration is further challenged by data that is increasingly hybrid, varied, and changing. The emergence of IoT, increasing analytics requests and rising complexity of ETL jobs all contribute to the need for a more flexible solution.

Data fabrics vs. data integration

Data fabrics have emerged as a modern solution that leverage existing investments in data integration and data catalogs and provide the needed flexibility through a layered knowledge graph. The knowledge graph component of the data fabric maps entities, their metadata, and their relationships in an evolving network for faster data delivery across the organization.

What is unique about Stardog is that it can represent information of any form or structure, providing a truly universal view of all the information that matters most to the business. By incorporating virtualization into Stardog’s platform, data duplication and redundancy is avoided, ensuring you work with correct and current data—and concerns around costs and scale are mitigated through virtualization’s limitless growth potential.

  • In a data fabric approach, one of the most important components is the development of a dynamic, composable and highly emergent knowledge graph that reflects everything that happens to your data. This core concept in the data fabric enables the other capabilities that allow for dynamic integration and data use case orchestration.

    - Gartner, How to Activate Metadata to Enable a Composable Data Fabric,” Mark Beyer, Ehtisham Zaidi, 16 July 2020

Data Fabric: The Next Generation of Data Management

Build a data fabric to power collaborative, cross-functional projects and products. Escape reactive workflows with a resilient digital foundation.

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