Which Query Engine?

Which Vizzly Query Engine?

Vizzly is incredibly flexible. For example, we offer 4 different Query Engines to generate results for your dashboard, because we know "1 size fits all" solutions are never optimal.

Data is made available on Vizzly dashboards through the concept of data sets. Each data set contains a collection of fields, and each Query Engine provides purpose-built tools for building these data sets in a way best suited to your setup, and to execute queries against these data sets.

Next, we will explore the different options available to you, to find the one that fits your requirements the best.


Our in-browser solution enables you to connect to your existing APIs or GraphQL endpoints and pull in all of a user's data into the browser where our unique JS Query Engine powers all of the results needed for the dashboard.

This approach is the most flexible if each user does not have much data to load into the browser. It can operate in environments where each user has completely unique fields in their data set (dynamic) or if all the fields are consistent across data sets and users (normalized).

To start building with an In-browser Query Engine, create an "In-browser" project on your account.


If you are looking for a fast way of connecting to your normalized data that resides in your database or data warehouse, then the Cloud Query Engine is the right choice for you.

To start building with a Cloud Query Engine, create a "Cloud" project on your account.


This is a self-hosted solution to be used when the fields in your data sets are consistent between users. We call these normalized data sets.

Using this Query Engine, you will be able to build data sets using our UI or define them using SQL.

To start building with a normalized Query Engine, create a "Normalized" project on your account.


This is a self-hosted solution to be used when each of your users have a unique set of fields in their data sets. You will be able to programmatically build the data sets to make available to each of your users independently.

We call data sets built in this way, dynamic data sets.

To start building with a Dynamic Query Engine, create a "Dynamic" project on your account.