OpenMetadata/openmetadata-docs/content/v1.7.x/connectors/database/sqlite/yaml.md

---
title: Run the SQLite Connector Externally
description: Configure SQLite database connections in OpenMetadata with YAML. Step-by-step setup guide, configuration examples, and best practices for metadata extraction.
slug: /connectors/database/sqlite/yaml
---

{% connectorDetailsHeader
name="SQLite"
stage="PROD"
platform="OpenMetadata"
availableFeatures=["Metadata", "Data Profiler", "Data Quality", "View Lineage", "View Column-level Lineage", "dbt", "Sample Data", "Auto-Classification"]
unavailableFeatures=["Query Usage", "Owners", "Tags", "Stored Procedures"]
/ %}

In this section, we provide guides and references to use the SQLite connector.

Configure and schedule SQLite metadata and profiler workflows from the OpenMetadata UI:

- [Requirements](#requirements)
- [Metadata Ingestion](#metadata-ingestion)
- [Data Profiler](#data-profiler)
- [Data Quality](#data-quality)
- [Lineage](#lineage)
- [dbt Integration](#dbt-integration)

{% partial file="/v1.7/connectors/external-ingestion-deployment.md" /%}

## Requirements

### Python Requirements

{% partial file="/v1.7/connectors/python-requirements.md" /%}

To ingest basic metadata sqlite user must have the following privileges:
  - `SELECT` Privilege on `sqlite_temp_master`

## Metadata Ingestion

All connectors are defined as JSON Schemas.
[Here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/entity/services/connections/database/sqliteConnection.json)
you can find the structure to create a connection to SQLite.

In order to create and run a Metadata Ingestion workflow, we will follow
the steps to create a YAML configuration able to connect to the source,
process the Entities if needed, and reach the OpenMetadata server.

The workflow is modeled around the following
[JSON Schema](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/workflow.json)

### 1. Define the YAML Config

This is a sample config for SQLite:

{% codePreview %}

{% codeInfoContainer %}

#### Source Configuration - Service Connection

{% codeInfo srNumber=1 %}

**username**: Username to connect to SQLite. Blank for in-memory database.

{% /codeInfo %}

{% codeInfo srNumber=2 %}

**password**: Password to connect to SQLite. Blank for in-memory database.

{% /codeInfo %}

{% codeInfo srNumber=3 %}

**hostPort**: Enter the hostname and port number for your SQLite deployment in the Host and Port field.

{% /codeInfo %}

{% codeInfo srNumber=4 %}

**database**: The database of the data source is an optional parameter, if you would like to restrict the metadata reading to a single database. If left blank, OpenMetadata ingestion attempts to scan all the databases.


{% /codeInfo %}

{% codeInfo srNumber=5 %}

**databaseMode**: How to run the SQLite database. :memory: by default.

{% /codeInfo %}

{% partial file="/v1.7/connectors/yaml/database/source-config-def.md" /%}

{% partial file="/v1.7/connectors/yaml/ingestion-sink-def.md" /%}

{% partial file="/v1.7/connectors/yaml/workflow-config-def.md" /%}

#### Advanced Configuration

{% codeInfo srNumber=9 %}

**Connection Options (Optional)**: Enter the details for any additional connection options that can be sent to database during the connection. These details must be added as Key-Value pairs.

{% /codeInfo %}

{% codeInfo srNumber=10 %}

**Connection Arguments (Optional)**: Enter the details for any additional connection arguments such as security or protocol configs that can be sent to database during the connection. These details must be added as Key-Value pairs.

- In case you are using Single-Sign-On (SSO) for authentication, add the `authenticator` details in the Connection Arguments as a Key-Value pair as follows: `"authenticator" : "sso_login_url"`

{% /codeInfo %}

{% /codeInfoContainer %}

{% codeBlock fileName="filename.yaml" %}

```yaml {% isCodeBlock=true %}
source:
  type: sqlite
  serviceName: <service name>
  serviceConnection:
    config:
      type: SQLite
```
```yaml {% srNumber=1 %}
      username: <username>
```
```yaml {% srNumber=2 %}
      password: <password>
```
```yaml {% srNumber=3 %}
      hostPort: <warehouse>
```
```yaml {% srNumber=4 %}
      database: <database>
```
```yaml {% srNumber=5 %}
      databaseMode: <database-mode>
```
```yaml {% srNumber=9 %}
      # connectionOptions:
      #   key: value
```
```yaml {% srNumber=10 %}
      # connectionArguments:
      #   key: value
```


{% partial file="/v1.7/connectors/yaml/database/source-config.md" /%}

{% partial file="/v1.7/connectors/yaml/ingestion-sink.md" /%}

{% partial file="/v1.7/connectors/yaml/workflow-config.md" /%}

{% /codeBlock %}

{% /codePreview %}

{% partial file="/v1.7/connectors/yaml/ingestion-cli.md" /%}

{% partial file="/v1.7/connectors/yaml/data-profiler.md" variables={connector: "sqlite"} /%}

{% partial file="/v1.7/connectors/yaml/auto-classification.md" variables={connector: "sqlite"} /%}

{% partial file="/v1.7/connectors/yaml/data-quality.md" /%}

{% partial file="/v1.7/connectors/yaml/lineage.md" variables={connector: "sqlite"} /%}

## dbt Integration

You can learn more about how to ingest dbt models' definitions and their lineage [here](/connectors/ingestion/workflows/dbt).