SQLite Manager (n8n community node)

Manage local SQLite databases – including vector search with sqlite-vec – directly from your n8n workflows.

This package bundles a single node (sqliteManager) that can:

• discover and manage SQLite database files stored on the n8n host
• create or delete databases with optional bootstrap SQL
• execute arbitrary SQL (including vector KNN queries via sqlite-vec)
• return query results as structured JSON for downstream nodes

Use case examples

• Maintain lightweight knowledge bases for AI agents hosted in n8n
• Share local cache tables between workflows without an external DB
• Run ad‑hoc data migrations or maintenace scripts inside a workflow

• Requirements
• Installation
• Configuration
• Node operations
• Usage examples
• Development
• Support
• Version history

Requirements

| Component | Version / notes | | -------------------- | -------------------------------------------------- | | n8n | 1.114.4 or newer (tested in Docker & desktop) | | Node.js | 22.x (matches upstream n8n release) | | SQLite CLI | ≥ 3.49 with JSON output support (sqlite3 -json) | | sqlite-vec | Bundled automatically during Docker build | | File system | Write access to the directory storing databases |

The node does not require external credentials or APIs. All operations happen on the local file system of the n8n host/container.

Installation

From the n8n UI (recommended)

1. Open Settings → Community Nodes → Install.
2. Enter the package name: n8n-nodes-rckflr-sqlitemanager.
3. Acknowledge the community-node warning banner and confirm the install.
4. Reload the editor if the new icon does not appear immediately.

From the command line

cd ~/.n8n
pnpm install n8n-nodes-rckflr-sqlitemanager
pnpm build

Restart the n8n instance afterwards.

Docker / self-hosted images

Add the package to the N8N_COMMUNITY_NODES_INSTALL environment variable:

N8N_COMMUNITY_NODES_INSTALL=n8n-nodes-rckflr-sqlitemanager

The included Dockerfile in this repository demonstrates how we compile sqlite-vec at build time and mount persistent volumes for SQLite data and user-installed Python packages.

Configuration

The node looks up its working directory from the following environment variables:

| Variable | Default | Purpose | | ----------------------- | ------------------------- | ----------------------------------------- | | SQLITE_BASE_DIR | /opt/sqlite-db | Root directory where database files live. | | SQLITE_VEC_LIBRARY | /usr/local/lib/sqlite-extensions/vec0.so | Location of the compiled sqlite-vec shared object. | | SQLITE_VEC_ENTRYPOINT | sqlite3_vec_init | Entry point name inside the sqlite-vec module. |

Ensure that the directory referenced by SQLITE_BASE_DIR is writable by the user running n8n (inside Docker, usually the node user).

Node operations

| Operation | Parameters | Notes | | ---------------- | ------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------- | | List Databases | None | Returns one item per file (name, absolute path, sizeBytes, updatedAt). | | Create Database | databaseName, overwrite (boolean), initialSql (multiline string) | Creates or truncates a file. initialSql is executed immediately after creation. | | Delete Database | databaseName, ignoreMissing (boolean) | Deletes the file. When ignoreMissing=true the node emits a result but does not raise an error. | | Execute Query | databaseName, sql, returnData (boolean), failOnEmpty (boolean) | Runs SQL via the SQLite CLI. When returnData=true, results are parsed from the -json output. |

Vector queries work out of the box. For example:

SELECT headline, distance
FROM vec_articles
WHERE headline_embedding MATCH lembed('n8n automation')
  AND k = 5;

The node will automatically preload the sqlite-vec library before executing the statement.

Usage examples

1. Building a lightweight embeddings store

1. Use Create Database with an initialSql that defines a vec0 virtual table.
2. Insert embeddings generated elsewhere (or from an HTTP node).
3. Run Execute Query with a MATCH clause to retrieve similar content.

2. ETL on local CSV drops

1. Start the workflow when a new file arrives (e.g. via SFTP or HTTP).
2. Load the data into a temporary SQLite database with staging tables.
3. Run transformation SQL, then export the result to the next node.
4. Clean up the temporary database with Delete Database.

3. Operational maintenance

Schedule the node (using Cron plus Execute Query) to vacuum or analyze databases, and funnel results into Slack/email notifications if anomalies are detected.

Development

pnpm install
pnpm lint
pnpm build
pnpm dev   # launches a local n8n instance with hot-reload for the node

We rely on the official @n8n/node-cli for builds, linting, and publishing. Make sure you run pnpm build before committing to keep the transpiled artifacts in sync.

Automated tests

Run the end-to-end regression suite (requires sqlite3 and a compiled sqlite-vec library):

SQLITE_VEC_LIBRARY=/usr/local/lib/sqlite-extensions/vec0 \
SQLITE_VEC_ENTRYPOINT=sqlite3_vec_init \
pnpm test

The test script spins up a temporary database, creates a vec0 virtual table, inserts fixture vectors, and asserts that the nearest-neighbour query returns the expected record.

Project structure

nodes/
  SqliteManager/
    SqliteManager.node.ts    # Source TypeScript implementation
    SqliteManager.node.json  # Metadata consumed by n8n
    sqliteManager.svg        # Icon (light theme)
    sqliteManager.dark.svg   # Icon (dark theme)
dist/                        # Build output generated by `pnpm build`

Verification checklist for n8n

• [x] Package name starts with n8n-nodes-.
• [x] README includes installation, usage, compatibility, and support information.
• [x] MIT license file present.
• [x] n8n field in package.json declares provided nodes.
• [x] npm run lint and npm run build succeed.
• [x] No bundled secrets or credentials.

Support

Please open an issue on GitHub for bug reports or feature requests:
https://github.com/MauricioPerera/n8n-nodes-rckflr-sqlitemanager/issues

For consultancy or commercial support, reach out to Mauricio Perera at [email protected].

Version history

See CHANGELOG.md for a detailed release log.

• 0.1.0 – Initial public release submitted for n8n community verification.

License

Released under the MIT License.