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

# Supported Data Sources

> Complete list of data sources supported by Pylar, including databases, data warehouses, and business applications

## Overview

Pylar supports a wide range of data sources, from databases and data warehouses to business applications. This page provides a comprehensive list of all supported sources.

## Databases and Data Warehouses

These sources are indexed for querying while your data remains in its original location:

### Cloud Data Warehouses

* **BigQuery** - Google's serverless data warehouse
* **Snowflake** - Cloud data platform
* **Amazon Redshift** - AWS data warehouse
* **MotherDuck** - Serverless analytics platform
* **Databricks** - Unified analytics platform

### Relational Databases

* **PostgreSQL** - Open-source relational database
* **MySQL** - Popular open-source database
* **AlloyDB** - Google Cloud's PostgreSQL-compatible database
* **Supabase** - Hosted PostgreSQL service

### Additional Databases

* **Microsoft SQL Server**
* **Oracle Database**
* And more...

<Info>
  For databases and data warehouses, your data stays in its original location. Pylar indexes it for easier querying and executes queries on your infrastructure.
</Info>

## Business Applications

These sources sync data to Pylar Warehouse:

### CRM and Sales

* **Salesforce** - Customer relationship management
* **HubSpot** - Marketing and sales platform

### Collaboration and Productivity

* **Google Sheets** - Spreadsheet application
* **Airtable** - Database and collaboration platform

### Analytics and Marketing

* **Amplitude** - Product analytics
* **Mixpanel** - Product analytics
* **Segment** - Customer data platform

### Additional Applications

* And many more business applications...

<Info>
  Business Applications sync their data to Pylar Warehouse, enabling fast querying and analysis within Pylar's infrastructure.
</Info>

## Connection Types Comparison

| Feature            | Business Applications     | Databases/Data Warehouses  |
| ------------------ | ------------------------- | -------------------------- |
| Data Location      | Synced to Pylar Warehouse | Stays in original location |
| Query Execution    | On Pylar infrastructure   | On your infrastructure     |
| Data Freshness     | Periodic syncs            | Real-time queries          |
| Cross-Source Joins | Supported                 | Supported                  |
| Setup Complexity   | Simple (OAuth usually)    | Requires credentials       |
| IP Whitelisting    | Usually not required      | Often required             |

## IP Address for Whitelisting

For databases and data warehouses that require IP whitelisting:

**Pylar IP Address**: `34.122.205.142`

This is a permanently assigned IP address. Whitelist it in your database firewall settings to allow Pylar to connect.

<Warning>
  Most databases and data warehouses require whitelisting Pylar's IP address (34.122.205.142) in your firewall settings. This is crucial for establishing a secure connection.
</Warning>

## Connection Guides

### Databases and Data Warehouses

* [BigQuery](/learn/making-connections/connecting-bigquery) - Google Cloud data warehouse
* [Snowflake](/learn/making-connections/connecting-snowflake) - Cloud data platform
* [PostgreSQL](/learn/making-connections/connecting-postgresql) - Open-source database
* [MySQL](/learn/making-connections/connecting-mysql) - Popular database
* [Redshift](/learn/making-connections/connecting-redshift) - AWS data warehouse
* [MotherDuck](/learn/making-connections/connecting-motherduck) - Serverless analytics
* [Supabase](/learn/making-connections/connecting-supabase) - Hosted PostgreSQL

### Advanced Connections

* [SSH Connections](/learn/making-connections/connecting-via-ssh) - Secure SSH tunnel connections

## Choosing the Right Source Type

### Use Business Applications When

* You want data synced to Pylar for fast querying
* You need simple, OAuth-based authentication
* You're working with SaaS application data
* You want automated data refreshes

### Use Databases/Data Warehouses When

* You want to query data in place
* You need real-time data access
* You have existing database infrastructure
* You want to avoid data duplication
* You need to join across multiple sources

## Connection Naming

When connecting sources, follow these naming rules:

* ✅ **Allowed**: Lowercase letters, numbers, underscores
* ❌ **Not Allowed**: Capital letters, special characters, spaces

**Examples**:

* ✅ `production_db`
* ✅ `snowflake_analytics`
* ✅ `customer_data_v2`
* ❌ `Production DB`
* ❌ `snowflake-analytics`
* ❌ `Customer Data`

<Tip>
  Use descriptive names that indicate the source and purpose. This name will be used in SQL queries to reference the connection.
</Tip>

## Multiple Connections

You can connect:

* **Multiple instances** of the same source type (e.g., multiple Google Sheets)
* **Different sources** to the same workspace
* **Same source** to different workspaces

Each connection must have a **unique name** within your workspace.

## Next Steps

Ready to connect a specific source?

* [Connecting BigQuery](/learn/making-connections/connecting-bigquery) - Step-by-step BigQuery guide
* [Connecting Snowflake](/learn/making-connections/connecting-snowflake) - Step-by-step Snowflake guide
* [Connecting PostgreSQL](/learn/making-connections/connecting-postgresql) - Step-by-step PostgreSQL guide
* [Connection Security](/learn/making-connections/connection-security) - Security best practices

<Card title="Connect BigQuery" icon="database" href="/learn/making-connections/connecting-bigquery">
  Get started with connecting your first database
</Card>