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, the streams are the files in that folder, and your data is the contents of each file.

For example:

  • Car engine data

  • Game 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


An image of a Project in the serverless environment.


A stream is a collection of data (parameters, events, binary blobs 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


A timestamp is the primary key for all data in a stream.

We support nanosecond precision; 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!

Data Types

We currently support any parameter, event, metadata or blob that consist of numeric (double precision), string (UTF-8) and binary data (blobs).


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.


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.


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.

Binary data

Quix also supports any binary blob data.

With this data you can stream, process and store any type of audio, image, video or lidar data, or anything that isn’t supported with our parameter, event or metadata types.


A set of code which can be deployed as one Docker image.


A service that connects - bridge - data between two or more systems (one of them being Quix). A bridge can be deployed server-side or client-side depending on the application. deployed client or server side.


Any application code that is continuously running and does not perform complicated data processing. For example, a bridge, a function, a backend operation, or an integration to a third party service like Twilio.


Any application code that is continuously running, performs complex data processing like ML, and pub/sub’s from one or more topics.

Note: during development a model can be deployed as a job. For example, when training the model.


Any application code that is run once. For example, use a job to run a batch import of data from an existing data store (CSV, DB or DataLake etc).


Stream Writer API

A HTTP API used to send telemetry data from any source to a topic in the Quix platform.

Stream Reader API

A Websocket API used to stream any data directly from a topic to an external application. Most commonly used to send the results of a model or service to an application in real-time.

Catalogue API

An HTTP API used to query historic data in the Catalogue. Most commonly used for dashboarding, analytics and training ML models. Also useful to call hitoric data when running an ML model or to call historic data from an external application.

Portal API

An HTTP API used to interact with most portal-related features such as creation of Workspaces, Users, etc.