The following is a list of definitions to aid understanding of how to work with Quix and streaming data.


A Topic is a grouping context for the telemetry data coming from a single source. Very simplified, a topic is similar to a folder in a filesystem, and the telemetry streams are the files in that folder.

For example:

  • Car engine data
  • F1 2019 game telemetry data
  • Telemetry from one ECU on a Boeing 737

Topics are key to good data governance. Use them to organise your data by:

  • Grouping incoming data by type or source
  • Maintaining separate topics for raw, clean or processed data


A stream is a collection of data (parameters, events and metadata) that belong to a single session of a single source. For example: 

  • One journey for one car
  • One game session for one player 
  • One flight for one aeroplane


Parameters are values that develop over time. The Quix SDK supports numeric and string values.

For example:  

  • Crank revolution and oil temperature are two discrete engine parameters that begin to define the engine system.
  • Player position in X, Y and Z are three discreet parameters that begin to define the player location in a game.
  • Altitude, GPS LAT, GPS LONG and Speed are four parameters that begin to define the location and velocity of a plane in the sky.

Referring back to topics as a grouping context: we would recommend that each of these examples would be grouped into a single topic to maintain context.

Data Types

We currently support numeric (double precision) and string (UTF-8) values.

Nanosecond precision

We support parameter sampling down to 1 nanosecond; that’s 1 x 10-9 seconds or one-billionth of a second!

Nanosecond precision is at the bleeding edge of real-time computing and is primarily driven by innovation with hardware and networking technology; kudos to you if you have an application for it!


Events are a discrete occurrence of a thing that happens or takes place. 

For example: 

  • Engine start, engine stop, warning light activated 
  • Game started, match made, kill made, player won the race, lap completed, track limits exceeded, task completed
  • Takeoff, landing, missile launched, fuel low, autopilot engaged, pilot ejected  

Events are typically things that occur less frequently. They are streamed into the same topics as their respective parameters and act to provide some context to what is happening.

Start and stop events mark the beginning and end of data streams.

Data Types

We currently support string (UTF-8) values.


Metadata describes additional information or context about a stream. 

For example:  

  • License plate number, car manufacturer, car model, car engine type, driver ID, 
  • Game version, player name, game session type, game session settings, race car set-up
  • Flight number, destination, airport of origin, pilot ID, airplane type  

Metadata typically has no time context, rather it exists as a constant throughout one or more streams. For example, your metadata could be the configuration of a car that is sold from a dealership (such as engine size, transmission type, wheel size, tyre model etc); you could create a stream every time that car is driven by the owner, but the engine size and transmission type won’t change.

Metadata is key to data governance and becomes very useful in down-stream data processing and analytics.

Data Types

We currently support string (UTF-8) values.