Data Tables

Data Tables are lightweight, persistent, schema‑defined storage components built into Koodisi. They allow you to manage structured data without the need for external databases.

The new Tables menu combines both Lookups and Data Tables under a unified interface with separate tabs.

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Benefits

• Reusable data logic: Centralize your ID mappings, sync checkpoints, and configuration records.
• High performance: Optimized for quick access with optional TTL (Time to Live) caching.
• Declarative querying: Visual tools to filter, sort, group, and aggregate data without code.
• No external DB required: Eliminates infrastructure burden for transient or reference data.
• Seamless integration: Fully compatible with workflow activities.
• Scoped & secure: Bound by environment and role‑based access controls.

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How It Works

Creating Tables

1. Go to the Tables tab in the main navigation.
2. Choose to either create a table from scratch or import data from a CSV.
3. Define the schema: column names, types, and TTL in minutes.
4. Save the table for immediate use across workflows.

Using Tables in Workflows

You can use purpose‑built activities to interact with your Data Tables:

• DataTableQuery – Retrieve data using filters, sorting, aggregation, and pagination.
• DataTableInsert – Insert new rows.
• DataTableUpdate – Update existing records based on matching conditions.
• DataTableUpsert – Insert or update data based on unique key(s).
• DataTableDelete – Remove specific rows using filter conditions.
• DataTableTruncate – Bulk delete entire tables or filtered subsets.

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DataTableQuery

Description

Retrieves data from tables using filters, sorting, aggregation, and pagination options.

Configuration

Field	Required	Description	Example
Name	Required	The name of the activity. This name must be unique in a workflow.	DataTableQuery
Description	Optional	A clear description to guide execution and collaboration.	Retrieves customer data filtered by status
Data Table	Required	A predefined resource for accessing the data table.	Select Data Table

Columns Tab

Field	Required	Description	Example
Column	Required	The name of the column in the table	name, age, id
Type	Auto	Data type of the column	string, number, boolean
Key	Optional	Indicates if it's a key column	Selected/Deselected

Conditions Tab

Field	Required	Description	Example
Condition Group	Optional	Named groups of conditions (AND/OR logic)	group_1, group_2
Column	Required	The column to apply the condition to	name, age, email
Type	Auto	Data type of the column	string, integer
Operator	Required	Comparison operator	=, !=
Filter Condition	Required	The value and logical operation	AND, Select Operation

Sorting Tab

Field	Required	Description	Example
Column Name	Optional	The column to sort by	name, id
Sort Type	Required	Direction of sort	Ascending, Descending

Aggregation Tab

Field	Required	Description	Example
Function	Required	Aggregation function	SUM, COUNT, AVG
Column	Required	Column to aggregate	id, age
Alias name	Optional	Name for the aggregated result	DemoFunction1

Input Schema

Field	Required	Data Type	Description	Example
Dynamically generated based on query configuration	Optional	Various	Mapping fields for conditions, columns, and other parameters	group_1.name, group_2.email

Output Schema

Field	Required	Data Type	Description	Example
dtQueryOutput	Required	Object	Container for all query results	–
records	Required	Array	The rows returned	–
totalCount	Required	Integer	Total number of records matching the query	156
hasMoreRecords	Required	Boolean	Indicates if more records exist beyond this page	true
nextOffset	Optional	Integer	Offset for retrieving the next page	100
executionTimeMs	Required	Integer	Query execution time in milliseconds	350

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DataTableUpsert

Description

Inserts new records or updates existing ones based on unique key(s).

Configuration

Field	Required	Description	Example
Name	Required	Unique name of the activity within a workflow.	DataTableUpsert
Description	Optional	Clear description for guidance and collaboration.	Updates product inventory or adds new products if absent
Data Table	Required	Predefined resource for accessing the data table.	regressiontest
TTL	Required	Time‑to‑live for the stored data (in seconds).	60

Columns Tab

Field	Required	Description	Example
Column	Required	The name of the column	name, age, id
Type	Auto	Data type	string, number
Key	Required	Column(s) used to identify records	Selected/Deselected

Input Schema

Field	Required	Data Type	Description	Example
records	Required	Array	Array of records to be upserted	–
record	Required	Object	Individual record matching selected columns	–

Output Schema

Field	Required	Data Type	Description	Example
dtUpsertOutput	Required	Object	Container for upsert operation results	–
rowsAffected	Required	Integer	Number of rows inserted or updated	5

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DataTableInsert

Description

Inserts new rows into a data table.

Configuration

Field	Required	Description	Example
Name	Required	Unique name of the activity.	DataTableInsert
Description	Optional	Clear description for guidance and collaboration.	Inserts new employee records
Data Table	Required	Predefined resource for accessing the data table.	regressiontest
TTL	Required	Time‑to‑live for the stored data (in seconds).	60

Columns Tab

Field	Required	Description	Example
Column	Required	The name of the column	name, age
Type	Auto	Data type	string, integer
Key	Optional	Indicates if it’s a key column	Selected/Deselected

Input Schema

Field	Required	Data Type	Description	Example
records	Required	Array	Array of records to be inserted	–
record	Required	Object	Individual record matching selected columns	–

Output Schema

Empty by default; extendable with custom fields such as:

Field	Required	Data Type	Description	Example
rowsAffected	Optional	Integer	Number of rows successfully inserted	5
success	Optional	Boolean	Indicates operation success	true
errors	Optional	Array	Details of any failed insertions	–

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DataTableDelete

Description

Removes specific rows from a data table using filter conditions.

Configuration

Field	Required	Description	Example
Name	Required	Unique name of the activity.	DataTableDelete
Description	Optional	Clear description for guidance and collaboration.	Removes obsolete customer records
Data Table	Required	Predefined resource for accessing the data table.	regressiontest

Conditions Tab

Field	Required	Description	Example
Condition Group	Optional	Named groups of conditions (AND/OR logic)	group_1, group_2
Column	Required	The column to apply the condition to	name, id, email
Type	Auto	Data type	string, number
Operator	Required	Comparison operator	=, !=
Filter Condition	Required	The value and logical operation	AND, Select Operation
Add Condition	Optional	Button to add additional conditions within a group	–
Add Condition Group	Optional	Button to add new condition groups	–

Input Schema

Field	Required	Data Type	Description	Example
conditions	Required	Object	Container for all condition groups	–
group_1, group_2, etc.	Optional	Object	Named condition groups matching columns	–
name, name_1, etc.	Optional	Various	Values for specified column conditions	"John", 42

Output Schema

Empty by default; extendable with custom fields such as:

Field	Required	Data Type	Description	Example
rowsAffected	Optional	Integer	Number of rows deleted	5
success	Optional	Boolean	Indicates operation success	true
errors	Optional	Array	Details of any failed deletions	–

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DataTableTruncate

Description

Bulk deletes all data from a table, effectively resetting it while maintaining the table structure.

Configuration

Field	Required	Description	Example
Name	Required	Unique name of the activity.	DataTableTruncate
Description	Optional	Clear description for guidance and collaboration.	Clears all records from staging
Data Table	Required	Predefined resource for accessing the data table.	regressiontest

Output Schema

Empty by default; extendable with custom fields such as:

Field	Required	Data Type	Description	Example
success	Optional	Boolean	Indicates operation success	true
rowsAffected	Optional	Integer	Number of rows deleted	1250
executionTimeMs	Optional	Integer	Time taken to execute the operation (ms)	350

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Operator Mapping Table

Display Label	Operator Value	Applies To	Notes / Logic
Equal To (=)	=	string, number, date, boolean	Most common comparison
Not Equal To (!=)	!= or &lt;&gt;	string, number, date, boolean	Both != and <> are valid in SQL
Greater Than (>)	&gt;	number, date	Not applicable for string or boolean
Less Than (<)	&lt;	number, date
Greater Than or Equal To (>=)	&gt;=	number, date
Less Than or Equal To (<=)	&lt;=	number, date
Between	BETWEEN	number, date	Requires two inputs; not for string/boolean
In	IN	string, number, date, boolean	Accepts multiple values (mapped to = ANY)
Not In	NOT IN	string, number, date, boolean	Converted to &lt;&gt; ALL
Like	LIKE	string	Pattern match
Not Like	NOT LIKE	string
Is Null	IS NULL	all types	Checks for no value
Is Not Null	IS NOT NULL	all types	Checks for presence of value

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UI Logic Rules (For Display)

Type	Allowed Operators
string	Equal To, Not Equal To, In, Not In, Like, Not Like, Is Null, Is Not Null
number	Equal To, Not Equal To, Greater Than, Less Than, Greater Than or Equal To, Less Than or Equal To, Between, In, Not In, Is Null, Is Not Null
date	Equal To, Not Equal To, Greater Than, Less Than, Greater Than or Equal To, Less Than or Equal To, Between, In, Not In, Is Null, Is Not Null
boolean	Equal To, Not Equal To, In, Not In, Is Null, Is Not Null