Integrate the LaunchDarkly (OAuth) API with the Snowflake API

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

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Popular LaunchDarkly (OAuth) 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 LaunchDarkly (OAuth) and Snowflake Actions#

Execute SQL Query with the Snowflake API

Execute a custom Snowflake query. See our docs to learn more about working with SQL in Pipedream.

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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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Query SQL Database with the Snowflake API

Execute a SQL Query. See our docs to learn more about working with SQL in Pipedream.

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Overview of LaunchDarkly (OAuth)#

Launch Darkly's API provides the means to automate feature flagging and manage experiments in your software delivery. This power, harnessed within Pipedream's serverless environment, can transform how you handle software deployment strategies, perform A/B testing, and control access to new features. The API's capabilities extend to updating flags, fetching flag statuses, and managing user segments, all of which can be integrated into sophisticated, automated workflows that react to external triggers or scheduled events.

Connect LaunchDarkly (OAuth)#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    launch_darkly_oauth: {
      type: "app",
      app: "launch_darkly_oauth",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://app.launchdarkly.com/api/v2/projects`,
      headers: {
        Authorization: `Bearer ${this.launch_darkly_oauth.$auth.oauth_access_token}`,
      },
    })
  },
})

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 snowflake from '@pipedream/snowflake';

export default defineComponent({
  props: {
    snowflake,
  },
  async run({ $ }) {
    // Component source code:
    // https://github.com/PipedreamHQ/pipedream/tree/master/components/snowflake
    
    return this.snowflake.executeQuery({
      sqlText: `SELECT CURRENT_TIMESTAMP()`,
      binds: [],
    });
  },
});

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