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

# Database Connectors & Semantic Models

Lyzr Agent Studio allows your AI agents to connect seamlessly with all leading **SQL** (Structured Query Language) and **NoSQL** data sources available in the market. This critical capability enables your agents to move beyond static, pre-loaded information and access, analyze, and reason over your organization's real, live operational data in real time.

This integration is the foundation for creating powerful **Data Query Agents**, which are often referred to as **Text-to-SQL Agents**. Once connected, your agent can:

1. **Receive** natural language questions from a user (e.g., "Show me last month's sales by region").
2. **Convert** that natural language question into an accurate, executable database query (such as a complex SQL statement).
3. **Execute** the query against the database.
4. **Process** the results and provide accurate, data-driven insights in clear, natural language back to the user in real time.

🎥 **Here’s a quick video on how to build a Text-to-SQL Agent:** [Watch Video](https://www.youtube.com/watch?v=yzn6xOGs9lk)

### The Role of the Semantic Model

Connecting an entire, complex, and often massive corporate database directly to a single agent is inefficient, resource-intensive, and provides excessive, irrelevant context. Lyzr solves this challenge by requiring the creation of a **Semantic Model**.

* **Definition:** A Semantic Model is a crucial conceptual layer that holds only a **relevant subset** of your database schema. It includes only the specific tables, columns, and relationships required for that particular agent's task.
* **Purpose:** By holding only the relevant information, the Semantic Model ensures:
  * **Optimal Performance:** The agent has a focused scope, which drastically improves the speed and accuracy of query generation and execution.
  * **Accurate Context:** It gives the agent the precise, necessary context to understand your data relationships and terminology, allowing it to generate highly accurate and context-appropriate queries.
  * **Data Governance:** It acts as a controlled boundary, ensuring the agent can only access the data authorized for its function, enhancing security.

### 🔌 Supported Database Connectors

Lyzr offers robust, built-in connectivity to a comprehensive range of popular and enterprise-grade data stores, covering major cloud and on-premise solutions.

The image below displays the variety of database connectors available within the Lyzr Agent Studio:

<img src="https://mintlify.s3.us-west-1.amazonaws.com/lyzrinc/assets/images/data1.png" alt="" />

| Type                 | Data Connector                     | Details                                                                              | Status          |
| :------------------- | :--------------------------------- | :----------------------------------------------------------------------------------- | :-------------- |
| **Relational (SQL)** | **PostgreSQL**                     | A powerful open-source object-relational database system.                            | Fully Supported |
|                      | **MySQL**                          | The world's most popular open-source relational database.                            | Fully Supported |
|                      | **Amazon Redshift**                | Amazon's fully managed, petabyte-scale cloud data warehouse service.                 | Fully Supported |
|                      | **Google BigQuery**                | Google Cloud's serverless, highly scalable, and cost-effective cloud data warehouse. | Fully Supported |
|                      | **Azure SQL**                      | Microsoft's intelligent, scalable, cloud database service.                           | Fully Supported |
|                      | **Microsoft SQL Server**           | The widely-used enterprise-level relational database management system.              | Fully Supported |
|                      | **Snowflake**                      | The cloud-based data platform known for its unique architecture and scalability.     | Upcoming        |
| **NoSQL**            | **MongoDB**                        | A leading general purpose, document-based distributed database.                      | Fully Supported |
| **Cloud/Data Lake**  | **Databricks**                     | Integration with the unified data platform for data engineering, ML, and analytics.  | Upcoming        |
| **Files**            | **File Upload (CSV, Excel, JSON)** | Direct connectivity for analyzing data stored in common flat file formats.           | Fully Supported |

***