OneData Software delivers solutions for Streaming IoT Data that leverage AWS’s IoT Core Rules Engine, IoT Events, and Amazon Kinesis to enable real-time, responsive, and secure data pipelines from device fleets. Their offering helps businesses connect IoT devices, define event/rule-based logic, route streaming data to analytics or downstream services, and act on data in motion, all while maintaining strong security and operational practices.

Core Functionalities

1. Real-Time Data Ingestion & Protocol Support

Devices connect via AWS IoT Core using MQTT, HTTPS, or LoRaWAN. As device telemetry streams in, the system captures these messages continuously.

2. Rules Engine for Event Processing

The IoT Core Rules Engine allows setting up filters, transformations, and routing logic: e.g. “if temperature > threshold, send to Lambda / Kinesis / SNS / external endpoint.” Helps in building reactive workflows.

3. Integration with Kinesis & Analytics

Streaming data can be fed into Amazon Kinesis for buffering, further transformation, aggregation, or storage; or into IoT Analytics for more structured real-time or near-real-time analytics. This enables dashboards, anomaly detection, trend monitoring.

4. Event Detection and IoT Events

For more complex event patterns (e.g. multiple conditions over time), OneData uses AWS IoT Events to model and detect these, then trigger actions such as alerts, notifications, or automated remediation.

5. Security, Filtering, and Transformation at Ingress

Only relevant data is passed onward; rules can discard irrelevant messages or perform transformations. Communications are secured, device identity and least privilege enforced.

6. Actions & Integration Points

Depending on rules or event detections, data can be routed to AWS Lambda, stored in Amazon S3, pushed into Kinesis Data Firehose, or passed to the analytics or AI/ML stack. Also used for alerts / dashboards.

7. Scalability and Operational Monitoring

As IoT deployments scale to many devices and high message volumes, OneData provides architectures that handle high throughput, low latency. They also include monitoring, logging, error handling, performance metrics.

8. Use Cases

e.g. manufacturing equipment monitoring, healthcare device streams, inventory / supply chain telemetry, agriculture sensors, etc. Real-world applications across industries.

Benefits:

• Immediate detection of critical events (e.g. failures, threshold breaches)

• Reduced manual overhead; automated workflows and responses

• Greater visibility into operations via live streaming metrics and dashboards

• Faster decision making supported by near-real-time data flows

• Scalable pipelines that grow with device and data volumes

• Secure handling of device data, ensuring compliance and trust