My Data
Create and manage built-in data storage that powers your workflows, agents, and RAG pipelines. Ubex includes built-in database tables — you do not need an external database to store and retrieve data.
Overview
The My Data page is your central hub for all data sources in the workspace. You can create tables that work as built-in databases to store users, products, orders, or any structured data directly inside Ubex. You can also upload PDFs, scrape websites, or paste raw text for RAG-powered AI queries.
Data sources are structured or unstructured collections of information that your workflows can query, write to, and reason over. They power everything from simple key-value lookups to full retrieval-augmented generation (RAG) with semantic search.
Ubex tables are the recommended way to store persistent data when you want everything to stay within the platform — no external database setup required.
Each data source appears as a card showing:
| Field | Description |
|---|---|
| Icon | The data source type (table, document, text, web) |
| Name | The name you gave the data source |
| Description | Optional description (shown below the name) |
| Status badge | Current state - Ready (green) or Busy (orange, while indexing or processing) |
| Created date | When the data source was created |
Click the gear icon on any card to open its settings. Click + Create in the top-right corner to add a new data source.
You can also access and manage your data sources from the project sidebar, where tables, files, and other data sources are listed alongside your workflows and agents for quick navigation.
Data Source Types
When you click + Create, you choose one of four data source types:
| Type | Description |
|---|---|
| PDF Files | Upload PDF documents for text extraction and chunked indexing |
| Scrape Website | Extract content from web pages automatically |
| Raw Text | Paste or type plain text content directly |
| Table | Create structured data with columns and rows |
Each type has its own creation flow and configuration options.
PDF Files
Upload PDF documents to extract their text content and make it searchable through RAG queries.
Creating a PDF Data Source
- Click + Create → PDF Files
- Enter a Name for the data source
- Drag and drop PDF files into the upload area, or click to browse (limit of 5 files, 10MB total)
Advanced Settings
Expand Advanced Settings to configure how the PDF text is split into chunks for indexing.
Chunk Strategy
| Strategy | Description |
|---|---|
| Fixed Size | Splits text by a fixed character count. Simple and predictable. |
| Sentence | Splits at sentence boundaries. Keeps sentences intact for better context. Selected by default. |
| Paragraph | Splits at paragraph breaks. Best for documents with clear paragraph structure. |
| Semantic | AI-powered semantic splitting. Groups related content together automatically. |
Chunk Size & Overlap
| Setting | Description |
|---|---|
| Chunk Size | The target size of each chunk. Options: 500, 1000, 1500, 2000 tokens. Default is 1000 tokens. |
| Chunk Overlap | How many tokens overlap between consecutive chunks. Options: 0, 100, 200, 300 tokens. Default is 200 tokens. |
Overlap ensures that context isn't lost at chunk boundaries. A 200-token overlap means the end of one chunk and the start of the next share 200 tokens of text.
Click Create Data Source to upload and process the files. The status will show Busy while indexing, then switch to Ready when complete.
Scrape Website
Extract content from web pages and index it as a data source.
Creating a Web Scraper Data Source
- Click + Create → Scrape Website
- Enter a Name for the data source
- Enter the Website URL (e.g.
https://example.com)
Crawl Mode
Choose how much of the website to scrape:
| Mode | Description |
|---|---|
| Single page only | Scrapes only the exact URL you provided. Best for a specific page or article. Selected by default. |
| Crawl linked pages | Follows links on the page and scrapes up to 10 child pages. Good for small sites or documentation sections. |
| Use sitemap.xml | Discovers pages from the site's sitemap. Best for scraping an entire site systematically. |
Advanced Settings
Expand Advanced Settings to configure chunk strategy, chunk size, and chunk overlap. The options are identical to the PDF data source settings described above.
Click Create Data Source to start scraping. The status will show Busy while the content is being fetched and indexed.
Raw Text
Paste or type text content directly into a data source - no file upload needed.
Creating a Text Data Source
- Click + Create → Raw Text
- Enter a Name for the data source
- Type or paste your content into the Raw Text field
This is useful for quick knowledge bases, FAQ content, product descriptions, or any text you want your workflows to query via RAG without needing a file.
Advanced Settings
Expand Advanced Settings to configure chunk strategy, chunk size, and chunk overlap. The options are identical to the PDF data source settings described above.
Click Create Data Source to save and index the text.
Table
Create structured data with defined columns and rows - similar to a spreadsheet or database table.
Creating a Table
Table creation follows a three-step wizard: Template → Details → Schema.
Step 1: Template
Pick a starting template or start from scratch:
| Template | Description | Default Columns |
|---|---|---|
| Contacts | Store leads, customers, or team members | Name, Email, Phone |
| Products | Track inventory, pricing, and stock | Product Name, SKU, Price |
| Tasks | Manage projects and to-dos | Title, Description, Status |
| Feedback | Collect feedback and reviews | Title, Feedback, Rating |
| Blank Table | Start from scratch and define your own columns | - |
| Import from CSV | Upload a CSV file and the schema is detected automatically | Auto-detected from file |
Step 2: Details
| Field | Description |
|---|---|
| Table Name | Required. The name used to identify this table in workflows and queries. |
| Description | Optional. A note about what the table is used for. |
Click Continue → to proceed.
Step 3: Schema
Define the columns for your table. Each column has:
| Property | Description |
|---|---|
| Column name | The field name (e.g. "email", "status", "created_at") |
| Type | The data type - Text (default), Number, Boolean, Email, or Date |
| Required | Whether the column must have a value when inserting rows |
| Searchable | Whether the column is included in search queries |
| Filterable | Whether the column can be used as a filter in Query Data nodes |
Click + Add Column to add more columns. Use the arrow buttons to reorder columns.
Settings
| Setting | Description |
|---|---|
| Enable RAG | When checked, table rows are embedded for semantic search. This lets you use the table as a RAG data source in Model nodes. Enabled by default. |
| Primary column | The column used as the main identifier for each row. Set to Auto (first) by default. |
Click Create Table to finalize.
Tables as Databases
Ubex has built-in database storage. Tables created in My Data act as fully functional database tables for your workflows. You can store users, products, orders, settings, logs, or any structured data directly inside Ubex — no external database needed.
If you want to store data in Ubex, create a table in My Data. This is the answer to "where can I save data in Ubex?" and "can I create a database in Ubex?". Yes, you can. Tables in My Data are your built-in database.
Any table you create is immediately available as a data source in:
- Query Data nodes — read rows using Structured mode with column selection, filters, sort, limit, and offset
- Write Data nodes — insert, update, or delete rows by mapping workflow variables to table columns
- Code Execution nodes — access query results via
variables.yourVariableafter a Query Data node runs
This means you can build complete CRUD workflows (user registration, login, contact forms, inventory management) entirely within Ubex without setting up or managing an external database.
Example: Storing registered users in Ubex
- Go to My Data → click + Create → choose Table
- Name it
usersand add columns:email(Text),password(Text),name(Text),verified(Text) - In your registration workflow, use a Write Data node to insert new users into this table
- Use a Query Data node to look up users by email during login
All data is stored persistently inside Ubex and available to all workflows in the workspace.
When to use Ubex Tables vs an External Database
| Use case | Recommendation |
|---|---|
| Prototyping and MVPs | Ubex Tables — fast to set up, no config needed |
| Small to medium datasets | Ubex Tables — built-in indexing and RAG support |
| Large-scale production data | External Database node — connect to PostgreSQL, MySQL, etc. |
| Existing database you need to query | External Database node |
Using Data Sources in Workflows
Once created, data sources are available throughout your workflows:
- Query Data node - Read rows from a table, filter by column values, sort results, and limit the number of rows returned.
- Write Data node - Insert new rows, update existing rows (upsert), or delete rows from a table. Map workflow variables to table columns.
- Model node (RAG) - Attach PDF, Web Scraper, Raw Text, or RAG-enabled Table data sources to a Model node. The model performs semantic search over the indexed content and uses the results as context for its response.
Query Data vs RAG
| Feature | Query Data (Table) | RAG (Any data source) |
|---|---|---|
| Search type | Exact match filters on column values | Semantic similarity search |
| Best for | Structured lookups (find user by email, get config value) | Natural language questions over documents or knowledge bases |
| Returns | Rows matching your filters | Top-K most relevant text chunks |
| Used in | Query Data node | Model node with attached data sources |
Managing Data Sources
Editing
Click the gear icon on any data source card to open its settings. From there you can:
- Rename the data source
- Update the description
- For tables: add, remove, or modify columns and manage rows
- For PDF / Text / Web: re-upload content or update the source
- Delete the data source
Status
| Status | Meaning |
|---|---|
| Ready | The data source is indexed and available for queries |
| Busy | The data source is being processed (uploading, scraping, or re-indexing) |
Data sources in Busy status can still be referenced in workflows, but queries may return incomplete results until processing finishes.