> ## Documentation Index
> Fetch the complete documentation index at: https://docs.embeddingsync.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Create a Sync

> Quickstart guide to getting your data and embeddings in sync.

## 📌 What You'll Need

* A Postgres database with data you'd like to embed *(you can use Supabase for a free account)*.
* An account with Pinecone *(you can sign up for a [free account here](https://app.pinecone.io/?sessionType=signup))*.
* Postgres credentials including host, database name, port, username, and password.
* A Pinecone API key.

<Info>
  **Note**: Make sure you have all the necessary permissions to connect to your
  databases and generate API keys.
</Info>

## 🚀 Getting Started

### Step 1: Access the New Sync Form

[Signup](https://embeddingsync.com/signup) for a free (or [paid](https://embeddingsync.com/#pricing)) account on Embedding Sync.

Navigate to the ["New Sync" tab](https://embeddingsync.com/new-sync) in the Embedding Sync dashboard to get started.

### Step 2: Database Connection Details

Fill in the following fields related to your Postgres database:

1. **Host**: The address of your database server.
2. **Database**: The name of your Postgres database.
3. **Port**: The port number on which your database is running.
4. **Username**: Your Postgres username.
5. **Password**: Your Postgres password. (Note: We store this securely using AES256 industry-standard encryption.)

<CodeGroup>
  ```json theme={null}
  {
    "host": "db.yourhost.supabase.co",
    "database": "postgres",
    "port": 5432,
    "username": "postgres",
    "password": "yourpassword"
  }
  ```
</CodeGroup>

<Info>
  If you're using **Supabase**, you can find this info in `Project Settings` on
  the sidebar > `Database` > `Connction Info`.
</Info>

### Step 3: Embedding Details

Now, specify the data you want to embed:

1. **Table Name**: The database table containing the data to be embedded.
2. **Embedding Column Name**: The specific column you'd like to use for generating embeddings.
3. **Primary Key Column Name**: The column that serves as the unique identifier for each row.
4. **Updated At Column Name**: The column used to determine newly added or updated rows to sync. If a previously embedded row is updated, the new value will be updated in the vector store overriding the previous value.
5. **Pinecone Key**: Your Pinecone API key. Once logged into Pinecone, go to `API Keys` in sidebar > `+ Create API Key`.
6. **Embedding Model**: Choose the embedding model you'd like to use. Options include OpenAI's `text-embedding-ada-002` and HuggingFace `sentence-transformers/all-MiniLM-L6-v2`.

<Info>
  **Choosing an Embedding Model**: Understanding the trade-offs can help you pick the right model for your needs:

  * **text-embedding-ada-002**: This is a more powerful, larger model by OpenAI. It generates embeddings with 1536 dimensions. While it offers better performance, it will cost more to store these embeddings in Pinecone.

  * **sentence-transformers/all-MiniLM-L6-v2**: This is a smaller, faster model that's good for most simple use cases. It produces embeddings with 384 dimensions. The embeddings are around a fifth the size of OpenAI's, costing roughly 1/5th as much to store in Pinecone.

  **Query Path Considerations**: If you're using OpenAI, generating an embedding for your query string to query Pinecone is straightforward using their API. For the sentence-transformers model, you can either self-host to generate the query embedding or use our query API, which wraps the query embedding and Pinecone API call for you.
</Info>

<CodeGroup>
  ```json theme={null}
  {
    "table_name": "articles",
    "embedding_column_name": "content",
    "pk_column_name": "id",
    "updated_at_column_name": "updated_at",
    "pinecone_key": "your-pinecone-key",
    "embedding_model": "sentence-transformers/all-MiniLM-L6-v2"
  }
  ```
</CodeGroup>

### Step 4: Submit

Click the "Submit" button to initiate the sync. The process will now begin, and your data will be synchronized with your Pinecone vector database. It may take a few minutes for the sync to begin processing.

## 🛠 Troubleshooting

<AccordionGroup>
  <Accordion title="Sync not working">
    Check your database credentials and Pinecone API key. Make sure all details
    are correctly entered.

    If your Pinecone project is not in the `us-west1-gcp` Environment, please (contact us)\[mailto:[vimota@embeddingsync.com](mailto:vimota@embeddingsync.com)].
  </Accordion>

  <Accordion title="Getting an unknown error">
    Please (contact us)\[mailto:[vimota@embeddingsync.com](mailto:vimota@embeddingsync.com)] with the error details, we'll debug you asap.
  </Accordion>
</AccordionGroup>

<Footer>
  For more details and advanced configurations, check out our [Advanced
  Guide](/advanced-guide).
</Footer>