Data Stores

Data stores provide managed key-value storage for your workflows. Use them to persist data across executions, maintain state between steps, and build lookup tables — all scoped to your organization and accessible from any workflow.

How Data Stores Work

Data is organized into tables, each containing key-value entries. Tables are shared across all workflows in your organization, so any workflow can read or write to any table.

Concept	Description
Table	A named collection of key-value entries (like a database table)
Key	A unique identifier within a table (up to 1,024 characters)
Value	Any JSON-serializable data — strings, numbers, booleans, objects, or arrays

Creating a Table

Tables are created automatically when you first write to them using a data store step. You can also create tables from the Data Store page in the sidebar, or from the data store step configuration — the table name dropdown lets you select existing tables or type a new name to create one.

Data Store Steps

QuickFlo provides five step types for working with data stores. Each step is configured through the visual form builder in the workflow editor.

Get

Retrieve a single value by key.

Field	Description
Table	Select or type a table name
Key	The key to look up (supports templates, e.g., user-{{ initial.userId }})

Output available to later steps:

{{ get-user.value }}       // the stored value (or null if not found)
{{ get-user.found }}       // true or false
{{ get-user.value.email }} // access nested fields from stored objects

Set

Store or update a value. If the key already exists, its value is replaced.

Field	Description
Table	Select or type a table name
Key	The key to store under (supports templates)
Value	Key-value pairs defining the data to store
Expiration	Optional TTL — the entry is auto-deleted after this time

Expiration Settings

Option	Description
No expiration	Entry persists until manually deleted (default)
Custom TTL	Set a duration from 1 minute to 1 year

Tip

When expiration is enabled, the default TTL is 30 days. You can disable expiration entirely to keep entries indefinitely.

Output:

{{ set-user.success }}   // true if stored successfully
{{ set-user.key }}       // the key that was written

List

List all keys in a table with optional substring filtering on the key name.

Field	Description
Table	The table to list keys from
Key contains	Optional — return only keys whose name contains this substring (case-insensitive). Note: this is a substring/contains match, not a strict prefix.
Limit	Max results to return (1–1,000, default 100)
Offset	Skip this many results (for pagination)

Output:

{{ list-keys.keys }}      // array of key strings
{{ list-keys.total }}     // total matching keys
{{ list-keys.hasMore }}   // true if more results exist

Query

Search entries by their stored values using field-level filters — like a simple database query.

Field	Description
Table	The table to query
Filters	One or more conditions on value fields
Filter Mode	All (every filter must match) or Any (at least one must match)
Limit	Max results (1–1,000, default 100)
Offset	Skip results for pagination

Each filter has three parts:

Part	Description	Example
Field	Dot-notation path into the stored value	status, user.email, tags
Operator	Comparison type	equals, contains, greater than, etc.
Value	The value to compare against	active, 100, true

Available operators:

Operator	Description
equals	Exact match
not_equals	Not equal
contains	Text contains substring
array_contains	Array includes a value
gt	Greater than
gte	Greater than or equal
lt	Less than
lte	Less than or equal

Output:

{{ query-users.entries }}           // array of { key, value } objects
{{ query-users.entries[0].key }}    // first result's key
{{ query-users.entries[0].value }}  // first result's value
{{ query-users.total }}             // total matches
{{ query-users.hasMore }}           // true if more results exist

Delete

Remove a single entry by key.

Field	Description
Table	The table to delete from
Key	The key to delete (supports templates)

Output:

{{ delete-user.deleted }}   // true if the key existed and was deleted
{{ delete-user.key }}       // the key that was deleted

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Browsing Data in the UI

The Data Store page lets you browse, search, edit, and manage your data store entries directly from the QuickFlo UI.

Tables Sidebar

The left sidebar lists all tables in your organization with record counts. Use the search field at the top to filter tables by name. You can also create new tables or refresh the list from the toolbar icons.

Records Table

Selecting a table shows all its entries in a sortable table with Key, Created, and Updated columns. Each row has edit and delete action buttons. Click any row to open the detail panel.

Detail Panel

Clicking a record opens a detail panel showing:

• Metadata — size, created date, updated date, and expiry countdown (if set)
• Value preview — the full stored value with syntax highlighting and expandable tree view
• Clickable values — click any primitive value in the tree to quickly filter by it

From the detail panel you can edit, delete, or copy the key.

Searching and Filtering

The search bar supports two modes:

Key search — type any text to filter entries by key (case-insensitive contains match):

user-123

Value search — use field:value syntax to filter by stored values. Click the Search button or press Enter to execute:

Syntax	Description	Example
field:value	Field contains value (partial match)	status:active
field:=value	Field equals value (exact match)	email:=john@example.com
field:!value	Field does not contain value	status:!deleted
field:!=value	Field does not equal value	status:!=inactive
[].field:value	Array element field contains value	[].level:123
field[]:value	Array field contains primitive value	tags[]:important

Active filters appear as badges below the search bar that you can dismiss individually.

Editing Records

Click the edit icon on any record (or from the detail panel) to open the edit dialog. The editor supports two modes:

• Properties mode — visual path/value pairs with an “Add Property” button
• JSON mode — raw JSON editor for complex values

You can also toggle Set expiration to add or remove a TTL on the entry.

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Import and Export

Export

Export an entire table as a JSON file from the table toolbar. The export contains an array of key-value objects.

Import

Import data from JSON or CSV files into a table. The import dialog supports drag-and-drop file upload and shows a preview of entries before importing. Existing keys are updated (upsert) and new keys are created.

Note

Bulk import supports up to 50,000 entries per operation. Entries are processed in batches of 500 for memory efficiency, so very large imports stream through without holding the full payload in memory.

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Common Patterns

Storing Workflow State

Persist data across workflow executions — for example, tracking which records have been processed to prevent duplicates:

Step	Configuration
Get	Table: processed-records, Key: {{ $item.id }}
If	Condition: {{ get-record.found }} equals false
Set (in Then branch)	Table: processed-records, Key: {{ $item.id }}, Value: {{ $util.now }}

Building Lookup Tables

Store reference data that multiple workflows can use:

Step	Configuration
Set	Table: config, Key: region-mapping, Value: JSON with region mappings
Get (in another workflow)	Table: config, Key: region-mapping

Access nested values: {{ get-config.value.US }}

Counters and Accumulators

Increment a counter across workflow executions:

Step	Configuration
Get	Table: metrics, Key: daily-count
Set	Table: metrics, Key: daily-count, Value: {{ get-count.value | default: 0 | plus: 1 }}

Caching Expensive Operations

Use a data store with a TTL to avoid repeating expensive API calls across executions:

1. Get step: Look up the cache key
2. If step: Check {{ get-cache.found }}
   • Then branch: Use the cached value
   • Else branch: Call the API, then Set the result with a TTL (e.g., 1 hour)

Note

Data stores are persisted to disk, so they’re best suited for caching data that doesn’t change frequently (minutes to days). For sub-second caching needs, consider external caching services via HTTP steps.

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Sharing Tables Across Organizations

You can grant read-only access to a specific data store table from your organization to a partner organization. This is the foundation for cross-org analytics and partner dashboards — the partner can build dashboards on the shared table without ever seeing the rest of your data.

Creating a Share

From the data store table menu, choose Share with another organization and pick the target org. The user creating the share must belong to both organizations — the picker only shows orgs you’re a member of.

Field	Description
Source table	The table you’re sharing (read-only)
Target organization	The org that gains read access
Alias	Optional display name the partner sees instead of the raw table name

Creating or revoking a share requires the data-stores:admin role. Listing existing shares only requires data-stores:view.

What the Partner Sees

In the partner organization, the shared table appears as a data source in the dashboard builder, marked with a “shared from” badge so it’s clear it’s coming from another org. They can build pivot tables, charts, calculated fields, and global filters on top of it just like a native table — the analytics engine swaps in the owner org’s ID for WHERE clauses on shared queries.

Revoking a Share

Click Revoke on a share at any time. Revocation is a soft delete (so audit history is preserved) and takes effect immediately — any in-flight queries finish, but new queries against the shared table from the partner org return an error and any partner widgets backed by the share surface that error inline.

Note

Shares are read-only and table-scoped. The partner can’t write to your tables, can’t see other tables in your org, and can’t share your table further. If you need to grant write access too, do it via a workflow trigger the partner can call.

Visualizing Data

Any data store table can be turned into a dashboard with charts, pivot tables, filters, and calculated fields — no extra schema, no separate analytics database. Point a data source at the table and you’re done. See Dashboards for the full walkthrough.

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Limits

Limit	Value
Key length	1,024 characters
Table name length	255 characters
Minimum TTL	1 minute
Maximum TTL	No expiration (entries persist indefinitely)
Default TTL (when expiration enabled)	30 days
Query limit per request	1,000 entries
Bulk import per request	50,000 entries