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Enrich your Pinecone vector search with structured data from MySQL. Latenode's visual editor makes it easy to build AI-powered applications using no-code blocks and custom JavaScript, scaling affordably as your needs grow.
Connect Pinecone and MySQL in minutes with Latenode.
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In the workspace, click the “Create New Scenario” button.

Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Pinecone, triggered by another scenario, or executed manually (for testing purposes). In most cases, Pinecone or MySQL will be your first step. To do this, click "Choose an app," find Pinecone or MySQL, and select the appropriate trigger to start the scenario.

Select the Pinecone node from the app selection panel on the right.

Pinecone
Click on the Pinecone node to configure it. You can modify the Pinecone URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Next, click the plus (+) icon on the Pinecone node, select MySQL from the list of available apps, and choose the action you need from the list of nodes within MySQL.

Pinecone
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MySQL
Now, click the MySQL node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your MySQL settings. Authentication allows you to use MySQL through Latenode.
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Use various Latenode nodes to transform data and enhance your integration:

JavaScript
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AI Anthropic Claude 3
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MySQL
Trigger on Webhook
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Pinecone
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Iterator
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Webhook response
After configuring Pinecone, MySQL, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.
Run the scenario by clicking “Run once” and triggering an event to check if the Pinecone and MySQL integration works as expected. Depending on your setup, data should flow between Pinecone and MySQL (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
OpenAI ChatGPT + Pinecone + MySQL: When a message is sent to ChatGPT, the resulting text is used to create an embedding and stored in Pinecone. The original message and associated metadata are then stored in MySQL for future reference and optimized knowledge retrieval.
MySQL + Pinecone + Google Cloud Storage: When a row is updated in MySQL, update the corresponding vector embedding in Pinecone. Simultaneously, archive the old data by uploading it to Google Cloud Storage for long-term storage and compliance.
About Pinecone
Use Pinecone in Latenode to build scalable vector search workflows. Store embeddings from AI models, then use them to find relevant data. Automate document retrieval or personalized recommendations. Connect Pinecone with other apps via Latenode, bypassing complex coding and scaling easily with our pay-as-you-go pricing.
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About MySQL
Use MySQL in Latenode to automate database tasks. Read, update, or create records based on triggers from other apps. Streamline data entry, reporting, or inventory management. Latenode's visual editor simplifies MySQL integrations, allowing you to build scalable workflows with no-code tools or custom JavaScript logic.
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How can I connect my Pinecone account to MySQL using Latenode?
To connect your Pinecone account to MySQL on Latenode, follow these steps:
Can I synchronize Pinecone vector data with mySQL database?
Yes, you can. Latenode's visual editor simplifies data synchronization, allowing you to keep your Pinecone vectors consistent with your MySQL database automatically, saving time and ensuring accuracy.
What types of tasks can I perform by integrating Pinecone with MySQL?
Integrating Pinecone with MySQL allows you to perform various tasks, including:
HowdoIscalePineconeMySQLintegrationsto handlelargedatasets?
Latenode's architecture supports scaling your Pinecone and MySQL integrations efficiently, leveraging serverless functions and optimized data handling for large volumes.
Are there any limitations to the Pinecone and MySQL integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of: