Data Storage

• Overview
• Custom Tables
  • Creating a Table
  • Column Types
  • Limits
  • Managing Data in the UI
  • Script API
  • Context-Aware Methods (*For)
  • Filtering Operators
• Message Queues
  • Creating a Queue
  • Queue Dashboard
  • Message States
  • Limits
  • Message Browser
  • Script API
• When to Use Tables vs Queues
• Next Steps

Overview

JiBrok Studio for Jira Cloud provides two data storage mechanisms: Custom Tables for persistent structured data and Message Queues for asynchronous message processing.

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Custom Tables

SQL-backed structured storage accessible from both the UI and scripts.

Creating a Table

1. Navigate to the Tables tab
2. Click Create Table
3. Enter a table name
4. Define columns with name, type, and required flag

Column Types

Type	Description
String	Text values
Number	Numeric values
Boolean	True/false values
Date	Date values
Select	Dropdown from predefined options
JSON	Arbitrary JSON data

Limits

Limit	Value
Max tables	50
Max columns per table	30
Max rows per table	5,000
Max row data size	100 KB

Managing Data in the UI

• Add Row - opens a form with fields for each column
• Edit Row - click a row to modify values
• Delete Row - select rows and delete, or delete individually
• Search and Sort - filter rows by column values, sort ascending or descending

Script API

Access tables from scripts using the tables variable:

// Query rows with filtering
const rows = await tables.rows("Users", {
  where: { Status: { $eq: "active" } },
  orderBy: "-Age",
  limit: 10,
  offset: 0
})

// Add a row
await tables.addRow("Users", {
  Name: "Alice",
  Age: 30,
  Status: "active"
})

// Update a row
await tables.updateRow("Users", rowId, { Status: "inactive" })

// Delete a row
await tables.deleteRow("Users", rowId)

// Bulk insert multiple rows
await tables.addRows("Users", [
  { Name: "Bob", Age: 25, Status: "active" },
  { Name: "Carol", Age: 28, Status: "active" }
])

// Delete rows by filter (returns number of deleted rows)
const deleted = await tables.deleteRows("Users", { Status: { $eq: "inactive" } })
log(deleted)  // e.g., 3

// Find a single row
const row = await tables.findRow("Users", { Name: { $eq: "Alice" } })

// Count rows
const total = await tables.count("Users")
const active = await tables.count("Users", { Status: { $eq: "active" } })

Context-Aware Methods (*For)

When a table has a context configured (project/issue type restrictions), use *For methods. The issue parameter can be an issue object or a string key (e.g. "PROJ-123").

Method	Description
tables.getFor(name, issue)	Get schema with context check
tables.rowsFor(name, issue, options?)	Search with context check
tables.findRowFor(name, issue, where)	Find first with context check
tables.addRowFor(name, issue, data)	Insert with context check
tables.addRowsFor(name, issue, rows[])	Bulk insert with context check
tables.updateRowFor(name, issue, rowId, data)	Update with context check
tables.deleteRowFor(name, issue, rowId)	Delete with context check
tables.deleteRowsFor(name, issue, where)	Delete rows with context check
tables.countFor(name, issue, where?)	Count with context check

await tables.addRowFor("Logs", "PROJ-123", { Message: "Done" })
await tables.rowsFor("Logs", issue, { where: { Status: "open" } })

Filtering Operators

Operator	Description
$eq	Equal
$ne	Not equal
$gt	Greater than
$gte	Greater than or equal
$lt	Less than
$lte	Less than or equal
$like	Pattern match (SQL LIKE)
$in	In array of values

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Message Queues

Async message processing between scripts and triggers.

Creating a Queue

1. Navigate to the Queues tab
2. Click Create Queue
3. Enter a queue name

Queue Dashboard

The queue list shows:

• Queue name
• Message counts by status (Pending, Processing, Failed)
• Last activity time

Message States

State	Description
Pending	Waiting to be processed
Processing	Pulled by a consumer, awaiting acknowledgment
Failed	Rejected by a consumer

Limits

Limit	Value
Max queues	50
Max messages per queue	50,000
Max message payload size	100 KB

Message Browser

View messages filtered by status (Pending, Processing, Failed). Actions include:

Action	Description
Requeue	Move failed message back to pending
Delete	Remove individual message
Purge	Delete all messages (or by status)

Script API

Access queues from scripts using the queue variable:

// Push a message (with optional priority - higher = processed first)
await queue.push("tasks", { action: "process", data: "..." }, 5)

// Pull messages for processing
const messages = await queue.pull("tasks", 5)
for (const msg of messages) {
  // process msg.payload
  await queue.ack(msg.id)    // acknowledge success
  // or: await queue.reject(msg.id)  // mark as failed
}

// Consume (pull + auto-ack in one step)
const consumed = await queue.consume("tasks", 5)

// Peek without changing status
const preview = await queue.peek("tasks", 5)

// Requeue failed messages
await queue.requeue(messageId)

// Get queue size and stats
const size = await queue.size("tasks")
const stats = await queue.stats("tasks")

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When to Use Tables vs Queues

Use Case	Tables	Queues
Persistent data storage	Yes	No (messages are consumed)
Configuration/lookup data	Yes	No
Audit/history records	Yes	No
Task processing pipelines	No	Yes
Event-driven workflows	No	Yes
Cross-script communication	Possible	Designed for this
Priority-based ordering	No	Yes

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Next Steps

• Scripting Language - Full API reference
• Limits - All storage limits

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Related Docs

• Administration
• Jira Automation Integration
• FAQ & Troubleshooting
• Getting Started
• Global Variables