Embeddable

Embeddable is a developer toolkit for building fast, interactive customer-facing analytics. It works well with a high performance time-series database like QuestDB.

In Embeddable you define Data Models and Components in code, which are stored in your own code repository, then use the SDK to make these available for your team in the powerful Embeddable no-code builder. The end result is the ability to deliver fast, interactive customer-facing analytics directly into your product.

Built-in row-level security means that every user only ever sees exactly the data they’re allowed to see. And two levels of fully-configurable caching mean you can deliver fast, realtime analytics at scale.

Prerequisites​

  • A running QuestDB instance

Getting started with Embeddable​

Add a database connection using Embeddable API. This connection connects to your QuestDB instance. To add a connection, use the following API call:

// for security reasons, this must *never* be called from your client-side
fetch("https://api.embeddable.com/api/v1/connections", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    Accept: "application/json",
    Authorization: `Bearer ${apiKey}` /* keep your API Key secure */,
  },
  body: JSON.stringify({
    name: "my-questdb-db",
    type: "questdb",
    credentials: {
      host: "my.questdb.host",
      port: "8812",
      user: "admin",
      password: "quest",
    },
  }),
})

In response you will receive:

Status 201 { errorMessage: null }

The above represents a CREATE action, but all CRUD operations are available.

The apiKey can be found by clicking “Publish” on one of your Embeddable dashboards.

The name is a unique name to identify this connection.

  • By default your data models will look for a connection called “default”, but you can supply your models with different data_source names to support connecting different data models to different connections (simply specify the data_source name in the model)

The type tells Embeddable which driver to use

  • Here you'll want to use questbd, but you can connect multiple different datasources to one Embeddable workspace so you may use others such as: postgres, bigquery, mongodb, etc.

The credentials is a javascript object containing the necessary credentials expected by the driver

  • These are securely encrypted and only used to retrieve exactly the data you have described in your data models.
  • Embeddable strongly encourage you to create a read-only database user for each connection (Embeddable will only ever read from your database, not write).

In order to support connecting to different databases for prod, qa, test, etc (or to support different databases for different customers) you can assign each connection to an environment (see Environments API).