Real-time streaming and analytics platform for Big Data

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Real-time streaming and analytics platform for Big Data

Netcompany-Intrasoft’s Streamhandler is a high-performance cloud-based data streaming platform with hooks for ingesting and handling Big Data that can be offered as a Software as a service (SaaS). The platform based on Apache Kafka and its underlying technologies can support data integration, real-time and batch processing as well as training of machine learning and Deep Learning algorithms.

Specifically, Streamhandler’s capabilities include:

- real-time monitoring and event-specific processing;
- interoperability with modern data storage technologies and popular data sources and sinks;
- distributed messaging system;
- fault tolerance, resiliency to node failures and support of automatic recovery;
- security ensured through encryption, authentication and authorization;
- high scalability.

By providing a fully-fledged and AI-ready Big Data solution, Streamhandler has been proven to support data-intensive IT applications from cloud to edge in transport, mobility, insurance and health sectors.

While already a mature technology, by the end of the Convert2Green project, it will have been qualified as suitable for the operational environment where smart health, medical and IoT devices will be demonstrated and tested.

Input needed from customer

1. Define data types and structures for the different sources (e.g. sensing and metering equipment);
2. Specify (event-driven) use cases.

Specifications and Deliverables

1. Develop data collection and data exchange mechanisms to be implemented through connectors of providers and consumers;
2. Configure the Streamhandler platform to allow involved partners to be connected.

Value Proposition

Netcompany-Intrasoft’s Streamhandler offers data integration and analytics tools for traditional replication and batch-processing as well as modern data integration synchronisation and data visualisation to support a wide variety of use cases. By being developed in the context of research and innovation projects, additional capabilities to support real-time applications across industries (from manufacturing and tech to finance) are continuously added.

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