DataPump Service

The DataPump Service continuously pushes machine telemetry data from the Proemion DataPlatform into a customer-managed external cloud storage. Data arrives passively as it is transmitted from the telematics gateways — no active polling or request handling is required.

DataPump delivers time-series metrics - including position data - and Diagnostic Trouble Codes (DTCs). Time series data is exported as .csv files, DTCs as .json files.

The service is designed for customers who want direct access to their machine data — whether to build custom applications, ensure data ownership and portability or meet regulatory requirements such as the EU Data Act.

It is the recommended alternative to retrieving data via the REST API time series endpoint, particularly when large amounts of data need to be requested (e.g. for big data analytics) or high update rates where polling becomes inefficient.

The following diagram shows the data flow of the DataPump Service.

flowchart LR
    Machine -->|CAN Bus| CU[Communication Unit]
    CU -->|Cellular| DP[DataPlatform\nInterpretation]
    DP --> DPS[DataPump]
    DPS -->|CSV / JSON| CS[Customer\nCloud Storage]

Use Cases

The following use cases illustrate how customers are using DataPump to integrate machine data into their own systems and workflows.

Custom analytics platform integration DataPump enables customers to build their own big data applications, dashboards, or big data analytics solutions on top of the raw telemetry data delivered to their cloud storage.

EU Data Act compliance DataPump can be used to forward machine data to third parties as required under the EU Data Act, supporting obligations around user data access rights and switching of data processing services. The DataPlatform REST API can also be used for this purpose. See EU Data Act for further information.

Data ownership and portability Customers who want to retain a full copy of their machine telemetry data independent of the Proemion DataPlatform can use DataPump to continuously mirror data into their own storage infrastructure.

Comparison with REST API

For comparison, retrieving equivalent data via the REST API time series endpoint requires querying machines, signals, and timestamps individually — per machine and per signal — on every update cycle. At high update rates, this results in a large number of requests, making the REST API approach slow and inefficient for large fleets.

The REST API applies throttling and response size limits to protect service availability. For details, see the REST API throttling.

The following table summarizes the key differences between the two approaches:

Characteristic	REST API Time Series	DataPump Service
Data retrieval model	Pull (polling)	Push (event-driven)
Request overhead	High — per machine, per signal	None
Latency at high update rates	Increases with fleet size	Independent of fleet size
Implementation complexity	High — requires polling logic and state tracking	Lower — consume incoming files
Suitable for large fleets	Limited	Yes