Save resultset

Category: Function

Version: 1.0

Last updated: January 29, 2026

Author: Any2Info


Description

The Save resultset node is used to store and modify a resultset inside the Any2Info DataHub.

A resultset is a local dataset that is stored in the DataHub’s internal SQLite database. Resultsets can be reused across multiple dataflows within the same collection, making them ideal for caching, synchronization, and intermediate storage.

This node allows you to insert, update, delete, or fully replace the contents of a resultset based on the incoming data.


What is a resultset?

A resultset is:

  • A structured dataset stored locally in the DataHub

  • Persisted in an internal SQLite database

  • Accessible across dataflows within the same collection

  • Often used in combination with:

    • Resultset changed trigger

    • Resultset saved trigger

    • Dashboards and Forms


Configuration Options

Setting
Required
Description

Resultset

Yes

Selects the resultset to use. When editing this property, you can create or modify the underlying SQLite table structure.

Action

Yes

Determines how the incoming data is applied to the resultset.

Mapping

Yes

Defines how columns from the incoming dataset are mapped to columns in the resultset.


Resultset configuration

When creating or editing a resultset, you can define the table structure and special column roles.

Key column

  • Acts as a unique identifier for records

  • Required for all actions except Replace

  • Used to determine whether records should be inserted, updated, or deleted

Created column

  • Automatically filled with the current datetime when a record is inserted

  • Can only be assigned to columns of type Date or DateTime

  • Value is set only on insert

Updated column

  • Automatically filled with the current datetime when a record is inserted or updated

  • Can only be assigned to columns of type Date or DateTime


Action types

Replace

Replaces the entire contents of the resultset.

  • All existing records are removed

  • Incoming data is fully reinserted

  • No key column is required

  • Created and Updated columns are filled on insert


Insert

Inserts new records into the resultset.

  • Requires a key column

  • Records with an existing key are ignored

  • Only new records are added

  • Created is filled on insert

  • Updated is not modified


Update

Updates existing records in the resultset.

  • Requires a key column

  • Only records with a matching key are updated

  • Records without a matching key are ignored

  • Updated is automatically filled

  • Created remains unchanged


Insert or Update

Inserts new records or updates existing ones (upsert).

  • Requires a key column

  • If the key exists → record is updated

  • If the key does not exist → record is inserted

  • Created is filled on insert

  • Updated is filled on update


Delete

Deletes records from the resultset.

  • Requires a key column

  • Records matching the incoming keys are removed

  • Only the key column needs to be mapped


Except

Removes all records except those present in the incoming dataset.

  • Requires a key column

  • Records whose keys appear in the incoming data are removed

  • Inverse behavior of Delete


Mapping

The Mapping property defines how incoming columns are written to the resultset.

  • Not all resultset columns need to be mapped

  • Unmapped columns remain unchanged (except when using Replace)

  • For Delete and Except, usually only the key column is required


Usage

The Save resultset node is commonly used for:

  • Caching external API data

  • Sharing data between multiple dataflows

  • Triggering flows based on resultset changes

  • Persisting intermediate processing results


Tips & Best Practices

  • Use Replace for full refresh scenarios

  • Use Insert or Update for most synchronization use cases

  • Always define a key column when using any action other than Replace

  • Avoid using Save resultset in the same dataflow as a Resultset changed trigger to prevent loops

  • Keep resultsets focused and small for optimal performance


Changelog

Version
Date
Change

1.0

January 29, 2026

Initial documentation version added.

Last updated

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