Integrate the Snowflake API with the Data Stores API

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

Popular Ways to Connect Snowflake with Data Stores#

Add or update a single record with Data Stores API on New Row from Snowflake API

Snowflake + Data Stores

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Add or update multiple records with Data Stores API on New Row from Snowflake API

Snowflake + Data Stores

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Append to record with Data Stores API on New Row from Snowflake API

Snowflake + Data Stores

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Delete a single record with Data Stores API on New Row from Snowflake API

Snowflake + Data Stores

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Delete All Records with Data Stores API on New Row from Snowflake API

Snowflake + Data Stores

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Popular Snowflake and Data Stores 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 Snowflake and Data Stores Actions#

Add or update a single record with the Data Stores API

Add or update a single record in your Pipedream Data Store.

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Add or update multiple records with the Data Stores API

Add or update multiple records to your Pipedream Data Store.

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Append to record with the Data Stores API

Append to a record in your data store Pipedream Data Store. If the record does not exist, a new record will be created in an array format.

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Insert Multiple Rows with the Snowflake API

Insert multiple rows into a table

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Check for existence of key with the Data Stores API

Check if a key exists in your Pipedream Data Store or create one if it doesn't exist.

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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
  },
})

Overview of Data Stores#

Data Stores are a key-value store that allow you to persist state and share data across workflows. You can perform CRUD operations, enabling dynamic data management within your serverless architecture. Use it to save results from API calls, user inputs, or interim data; then read, update, or enrich this data in subsequent steps or workflows. Data Stores simplify stateful logic and cross-workflow communication, making them ideal for tracking process statuses, aggregating metrics, or serving as a simple configuration store.

Connect Data Stores#

export default defineComponent({
  props: {
    myDataStore: {
      type: "data_store",
    },
  },
  async run({ steps, $ }) {
    await this.myDataStore.set("key_here","Any serializable JSON as the value")
    return await this.myDataStore.get("key_here")
  },
})