Drasi

Drasi is an open-source real-time data infrastructure project that focuses on maintaining live, queryable views over data sources through event-driven change propagation (data infrastructure / event-driven systems).

• Real-time materialized views over connected data sources (data infrastructure).
• Event-driven change propagation and subscription-based access to updated views (event streaming / pub-sub).
• Graph-oriented model for representing and querying relationships across systems (graph data / data modeling).
• Integration with cloud-native environments under the Cloud Native Computing Foundation (cloud-native infrastructure).
• Support for building applications that react to data changes without custom polling logic (application integration / reactive systems).

More About Drasi

Drasi addresses the problem of keeping applications, services, and user experiences synchronized with underlying data sources in real time without relying on polling-heavy architectures. In many enterprise environments, operational data resides across operational databases, APIs, and microservices, and applications need a way to observe and consume changes as they happen. Drasi provides an event-driven (event-driven systems) foundation for maintaining live, queryable views over these sources so that consuming applications can work with current data with lower custom integration logic.

The project focuses on creating materialized views (data infrastructure) that stay continuously updated through change events, rather than requiring repeated full queries or manual synchronization processes. These views can be queried and subscribed to, enabling applications and services to receive updates as data changes propagate through the system. Drasi uses a connected or graph-oriented representation (graph data) to model relationships between entities across systems, which supports use cases where dependencies and links between datasets need to be preserved and traversed efficiently.

From a cloud-native perspective, Drasi is hosted under the Cloud Native Computing Foundation (CNCF), aligning it with patterns such as containerized deployment, declarative configuration, and interoperability with other CNCF ecosystem projects (cloud-native infrastructure). This positioning allows Drasi to be deployed on Kubernetes or similar platforms and to integrate into existing observability, security, and operations toolchains common in enterprise environments.

In enterprise or institutional environments, Drasi can be used as a shared data infrastructure layer for building dashboards, user-facing applications, and backend services that must react to data changes from multiple systems. Instead of each service implementing its own change detection and synchronization logic, teams can rely on Drasi to maintain real-time views and deliver updates via subscriptions (application integration / reactive systems). This pattern can reduce duplicate effort and supports consistent data semantics across consuming applications.

Technically, Drasi aligns with categories such as real-time data infrastructure, event-driven architectures, graph-based data modeling, and cloud-native middleware. Its focus on live, materialized views and event subscriptions positions it as a component that sits between data producers (databases, APIs, services) and data consumers (applications, services, and analytics tools). For directory and taxonomy purposes, Drasi fits within real-time data platforms, event-driven integration frameworks, and cloud-native data services used to enable responsive and reactive enterprise systems.