Integrate the Api Void API with the Snowflake API

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

Popular Api Void and Snowflake Triggers#

New Row from the Snowflake API

Emit new event when a row is added to a table

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New Query Results from the Snowflake API

Run a SQL query on a schedule, triggering a workflow for each row of results

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Failed Task in Schema from the Snowflake API

Emit new events when a task fails in a database schema

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New Database from the Snowflake API

Emit new event when a database is created

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New Deleted Role from the Snowflake API

Emit new event when a role is deleted

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Popular Api Void and Snowflake Actions#

Insert Multiple Rows with the Snowflake API

Insert multiple rows into a table

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Insert Single Row with the Snowflake API

Insert a row into a table

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Overview of Api Void#

With the Api Void API, you can build apps that:

Search for and analyze public APIs
Get detailed information about an API, including its methods, parameters, and
response data
Monitor an API for changes, and receive notifications when an API changes
Generate mock data for an API
Generate code samples for an API

Connect Api Void#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    api_void: {
      type: "app",
      app: "api_void",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://endpoint.apivoid.com/iprep/v1/pay-as-you-go/`,
      params: {
        key: `${this.api_void.$auth.api_key}`,
        ip: `{enter_ip_here}`,
      },
    })
  },
})

Overview of Snowflake#

Snowflake offers a cloud database and related tools to help developers create robust, secure, and scalable data warehouses. See Snowflake's Key Concepts & Architecture.

Getting Started

1. Create a user, role and warehouse in Snowflake

Snowflake recommends you create a new user, role, and warehouse when you integrate a third-party tool like Pipedream. This way, you can control permissions via the user / role, and separate Pipedream compute and costs with the warehouse. You can do this directly in the Snowflake UI.

We recommend you create a read-only account if you only need to query Snowflake. If you need to insert data into Snowflake, add permissions on the appropriate objects after you create your user.

2. Enter those details in Pipedream

Visit https://pipedream.com/accounts. Click the button to Connect an App. Enter the required Snowflake account data.

You'll only need to connect your account once in Pipedream. You can connect this account to multiple workflows to run queries against Snowflake, insert data, and more.

3. Build your first workflow

Visit https://pipedream.com/new to build your first workflow. Pipedream workflows let you connect Snowflake with 1,000+ other apps. You can trigger workflows on Snowflake queries, sending results to Slack, Google Sheets, or any app that exposes an API. Or you can accept data from another app, transform it with Python, Node.js, Go or Bash code, and insert it into Snowflake.

Learn more at Pipedream University.

Connect Snowflake#

import { promisify } from 'util'
import snowflake from 'snowflake-sdk'

export default defineComponent({
  props: {
    snowflake: {
      type: "app",
      app: "snowflake",
    }
  },
  async run({steps, $}) {
    const connection = snowflake.createConnection({
      ...this.snowflake.$auth,
      application: "PIPEDREAM_PIPEDREAM",
    })
    const connectAsync = promisify(connection.connect)
    await connectAsync()
    
    async function connExecuteAsync(options) {
      return new Promise((resolve, reject) => {
        connection.execute({
          ...options,
          complete: function(err, stmt, rows) {
            if (err) {
              reject(err)
            } else {
              resolve({stmt, rows})
            }
          }
        })
      })
    }
    
    // See https://docs.snowflake.com/en/user-guide/nodejs-driver-use.html#executing-statements
    const { rows } = await connExecuteAsync({
      sqlText: `SELECT CURRENT_TIMESTAMP()`,
    })
    return rows
  },
})