Working connectors
High-speed data flow from agreed sources, such as historians, event streams or business applications, into Databricks, Microsoft Fabric or your own lakehouse.
Real-time Data Connectors
Your operations change every second. Can your AI keep up?
Stream live data from historians, event streams, sensors and business applications into Databricks, Microsoft Fabric or your own lakehouse.
How it fits together
- Real-time sources
- High-speed connector
- Analytics + AI
What changes.
We build high-speed connectors for a wide variety of live systems and deliver every row to Databricks, Microsoft Fabric or your own lakehouse. When a source has no working connector, we build one.
Yours to put to work.
- Scope and acceptance criteria agreed together.
Recovery built in
Picks up where it left off after an interruption, backfills history, and checks for duplicates and gaps.
An operating handoff
Speed and delay monitoring, alerts, agreed data definitions and runbooks.
See an example engagement
An example scope, adapted to your environment.
- The starting point: Engineers want live compressor data from their plant historian, AVEVA PI, next to maintenance records in Databricks.
- The work: Connect agreed compressor readings, stream them into Databricks with backfill, and check values against source.
- The handoff: A monitored connector, agreed data definitions and recovery steps.
How we evaluate the result
- Data arrives as quickly as agreed, at full volume, under realistic load.
- Interruptions, restarts and backfills recover with no gaps or duplicate records.
- Values, units and timestamps match source records at their destination.
A useful place to start
Let’s work through your specific problem.
Start with Real-time Data Connectors, scoped to your environment.
Microsoft and Microsoft Fabric are trademarks of the Microsoft group of companies. AVEVA and PI are trademarks of AVEVA. Databricks is a trademark of Databricks, Inc.