Integrate the Supabase API with the BigML API

Setup the Supabase API trigger to run a workflow which integrates with the BigML API. Pipedream's integration platform allows you to integrate Supabase and BigML remarkably fast. Free for developers.

Popular Ways to Connect Supabase with BigML#

Create Batch Prediction with BigML API on New Row Added from Supabase API

Supabase + BigML

Try it

Create Batch Prediction with BigML API on New Webhook Event (Instant) from Supabase API

Supabase + BigML

Try it

Create Model with BigML API on New Row Added from Supabase API

Supabase + BigML

Try it

Create Model with BigML API on New Webhook Event (Instant) from Supabase API

Supabase + BigML

Try it

Create Source (Remote URL) with BigML API on New Row Added from Supabase API

Supabase + BigML

Try it

Popular Supabase and BigML Triggers#

New Row Added from the Supabase API

Emit new event for every new row added in a table. See documentation here

Try it

New Webhook Event (Instant) from the Supabase API

Emit new event for every insert, update, or delete operation in a table. This source requires user configuration using the Supabase website. More information in the README. Also see documentation here

Try it

New Model Created from the BigML API

Emit new event for every created model. See docs here.

Try it

New Prediction Made from the BigML API

Emit new event for every made prediction. See docs here.

Try it

Popular Supabase and BigML Actions#

Delete Row with the Supabase API

Deletes row(s) in a database. See the docs here

Try it

Create Batch Prediction with the BigML API

Create a batch prediction given a Supervised Model ID and a Dataset ID. See the docs.

Try it

Insert Row with the Supabase API

Inserts a new row into a database. See the docs here

Try it

Create Model with the BigML API

Create a model based on a given source ID, dataset ID, or model ID. See the docs.

Try it

Create Source (Remote URL) with the BigML API

Create a source with a provided remote URL that points to the data file that you want BigML to download for you. See the docs.

Try it

Overview of Supabase#

Supabase is a real-time backend-as-a-service that provides developers with a suite of tools to quickly build and scale their applications. It offers database storage, authentication, instant APIs, and real-time subscriptions. With the Supabase API, you can perform CRUD operations on your database, manage users, and listen to database changes in real time. When integrated with Pipedream, you can automate workflows that react to these database events, synchronize data across multiple services, or streamline user management processes.

Connect Supabase#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    supabase: {
      type: "app",
      app: "supabase",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://${this.supabase.$auth.subdomain}.supabase.co/rest/v1/`,
      headers: {
        Authorization: `Bearer ${this.supabase.$auth.service_key}`,
        "apikey": `${this.supabase.$auth.service_key}`,
      },
    })
  },
})

Overview of BigML#

The BigML API offers a suite of machine learning tools that enable the creation and management of datasets, models, predictions, and more. It's a powerful resource for developers looking to incorporate machine learning into their applications. Within Pipedream, you can leverage the BigML API to automate workflows, process data, and apply predictive analytics. By connecting BigML to other apps in Pipedream, you can orchestrate sophisticated data pipelines that react to events, perform analyses, and take action based on machine learning insights.

Connect BigML#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    bigml: {
      type: "app",
      app: "bigml",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://bigml.io/andromeda/source`,
      params: {
        username: `${this.bigml.$auth.username}`,
        api_key: `${this.bigml.$auth.api_key}`,
      },
    })
  },
})