Canadian no-code platform Flowfinity has launched Streams, a time series database to ingest and store massive amounts of machine-generated IoT data.

It is compatible with the firm’s flagship Actions software for workflow automation and data visualisation.

As industrial IoT applications continue to expand exponentially in the enterprise, organisations typically face a couple of common problems.

First, programming IoT hardware and sensors to be compatible with core ERP and scada systems can be difficult and expensive. Flowfinity has solved this by introducing the M1 controller, which provides out-of-the-box compatibility with all Flowfinity no-code software.

Secondly, once hardware and software are configured for IoT asset monitoring, how does one collect and store the data so they can be analysed and actioned on easily to provide value?

Streams is designed to ingest and store rapidly massive amounts of time series data, collected from IoT sensors and other automated data sources, using significantly less space than traditional relational data storage models.

Capable of storing billions of data records, Streams has an optimised ingestion engine that can process a CSV file containing over 100 million records in minutes, reducing processing time and resource use with better data processing capability.

Although capable as a stand-alone, the true power of Streams is unlocked by its seamless integration with Flowfinity Actions to merge machine and human driven workflows. Streams can trigger processes from incoming data and launch workflows in Actions via software automation robots when thresholds are reached, or other business rules are triggered.

For example, if monitoring sensor data from industrial equipment in a manufacturing or utilities setting to optimise runtime and maintenance schedules, Streams is used to accumulate usage statistics. When a threshold is reached, Streams will pass that variable to Actions where a software robot will create a preventative maintenance work order and notify the appropriate team members.

Once the maintenance has been completed, Actions will automatically reset the variable in the Streams time series, setting the stage for the next maintenance period and ensuring return from key assets.

Streams data can also be visualised in interactive operational dashboards to help make informed decisions. This includes step charts to see data easily that changes but remains static between changes for conditional monitoring of equipment status, as well as in maps. This shows precisely when a machine went offline or exceeded its optimal thresholds and for how long.