nLink Data Tables
The Data Tables node provides high-speed, natively integrated database operations. Instead of connecting to external databases like MySQL or Airtable, you can store your workflow's state, logs, and relational data directly within nLink. Enjoy sub-millisecond read/writes, automatic schema syncing, and extreme scalability.
What can you do with nLink Data Tables?
Sub-millisecond Performance
Because the database is natively integrated into the nLink Engine, read and write operations are performed locally without traversing the public internet, avoiding massive network latency.
Auto-Schema Synchronization
No need to write strict SQL DDL migrations. The node automatically analyzes your JSON payload and updates the Table Schema organically as your data structure evolves.
Advanced Query Filters
Retrieve data powerfully using nested conditional filters, sorting arrays, and limit/offset pagination to manage tables with millions of records without overflowing memory.
Detailed Usage & Configuration
The nLink Data Tables node replaces the need for external storage. It operates as a highly secure, ultra-fast key-value/relational hybrid data store built directly into your workspace.
1. Standard Operations
- Insert Record: Append new data gracefully. Map dynamic variables like
{{ $json.email }}to table fields. Ideal for saving webhook form submissions permanently. - Update Record: Provide the explicit
rowIdand a new payload. The engine will merge and update only the specified fields, preserving the rest of the record intact. - Get Many (Search): Perform complex queries to extract an array of records. You can apply filters (e.g.
Status = Active AND Age > 18), enforce Sorting, and set Pagination limits to retrieve exactly what your workflow needs. - Delete: Permanently eradicate a row based on its unique identifier.
2. The Schema Magic
Unlike rigid relational databases, nLink Tables are semi-schema-less. When you Insert a completely new JSON field that the table has never seen before, the system will automatically adapt and register the new field into the schema gracefully. This enables highly agile workflow development where the database shapes itself around your logic, not the other way around.