Pinecone
Long-term Memory for AI. The Pinecone vector database makes it easy to build high-performance vector search applications. Developer-friendly, fully managed, and easily scalable without infrastructure hassles.
Integrate the Pinecone API with the Snowflake API
Setup the Pinecone API trigger to run a workflow which integrates with the Snowflake API. Pipedream's integration platform allows you to integrate Pinecone and Snowflake remarkably fast. Free for developers.
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Popular Pinecone and Snowflake Triggers#
Popular Pinecone and Snowflake Actions#
Deletes one or more vectors by ID, from a single namespace. See the documentation.
Looks up and returns vectors by ID, from a single namespace.. See the documentation.
Searches a namespace, using a query vector. It retrieves the ids of the most similar items in a namespace, along with their similarity scores. See the documentation.
Updates vector in a namespace. If a value is included, it will overwrite the previous value. See the documentation.
Overview of Pinecone#
The Pinecone API enables you to work with vector databases, which are essential for building and scaling applications with AI features like recommendation systems, image recognition, and natural language processing. On Pipedream, you can create serverless workflows integrating Pinecone with other apps, automate data ingestion, query vector databases in response to events, and orchestrate complex data processing pipelines that leverage Pinecone's similarity search.
Connect Pinecone#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
pinecone: {
type: "app",
app: "pinecone",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.pinecone.io/collections`,
headers: {
"Api-Key": `${this.pinecone.$auth.api_key}`,
},
})
},
})
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: [],
});
},
});Trusted by 1,000,000+ developers from startups to Fortune 500 companies