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 MySQL API

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

Delete Vectors with Pinecone API on New Column from MySQL API
MySQL + Pinecone
 
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Delete Vectors with Pinecone API on New or Updated Row from MySQL API
MySQL + Pinecone
 
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Delete Vectors with Pinecone API on New Row (Custom Query) from MySQL API
MySQL + Pinecone
 
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Delete Vectors with Pinecone API on New Row from MySQL API
MySQL + Pinecone
 
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Delete Vectors with Pinecone API on New Table from MySQL API
MySQL + Pinecone
 
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New Column from the MySQL API

Emit new event when you add a new column to a table. See the docs here

 
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New or Updated Row from the MySQL API

Emit new event when you add or modify a new row in a table. See the docs here

 
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New Row from the MySQL API

Emit new event when you add a new row to a table. See the docs here

 
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New Row (Custom Query) from the MySQL API

Emit new event when new rows are returned from a custom query. See the docs here

 
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New Table from the MySQL API

Emit new event when a new table is added to a database. See the docs here

 
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Delete Vectors with the Pinecone API

Deletes one or more vectors by ID, from a single namespace. See the docs.

 
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Create Row with the MySQL API

Adds a new row. See the docs here

 
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Fetch Vectors with the Pinecone API

Looks up and returns vectors by ID, from a single namespace.. See the docs.

 
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Delete Row with the MySQL API

Delete an existing row. See the docs here

 
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Query IDs with the Pinecone API

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 docs.

 
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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

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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 MySQL

The MySQL application on Pipedream enables direct interaction with your MySQL databases, allowing you to perform CRUD operations—create, read, update, delete—on your data with ease. You can leverage these capabilities to automate data synchronization, report generation, and event-based triggers that kick off workflows in other apps. With Pipedream's serverless platform, you can connect MySQL to hundreds of other services without managing infrastructure, crafting complex code, or handling authentication.

Connect MySQL

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import mysql from '@pipedream/mysql';

export default defineComponent({
  props: {
    mysql,
  },
  async run({steps, $}) {
    // Component source code:
    // https://github.com/PipedreamHQ/pipedream/tree/master/components/mysql

    const queryObj = {
      sql: "SELECT NOW()",
      values: [], // Ignored since query does not contain placeholders
    };
    const { rows } = await this.mysql.executeQuery(queryObj);
    return rows;
  },
});