Developing Concepts πŸ“

Cool Stuff We're Thinking About

This section contains internal team notes on directions we're working. As it develops into complete features, we'll organize those features in the docs. Feel free to ask questions or make suggestions in the forums.

Data path


Datastore -> DatasourceType -> DSN -> Object ID -> Field Name

Object Lists

Individual Objects

Individual Object fields

Object slice ( one field

Object slice subset


Datastore is part of Core

Types are loaded as modules

Sources are added either automatically ( user login ) or manually ( datastore load callback )

Dynamic v. Pre-Loaded

? Query to e.g. google sheet






from Collection List ?wfu-data-dsn

object id



from GSheet CSV assigned name dsn Specific sheet!

row Spec identifies PK col or numeric row is used




( SA5 user object ) .data


















( aspect )

( item )

Dynamic Fields

e.g. Image metadata

? Is image EXIF preserved in the non-resized versions?

? If so, can we get it, or disable CTRL+O


RichText char count, word count...

<!DOCTYPE html>
<html lang="en">
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>EXIF Reader</title>
    <script src=""></script>

<img src="path_to_your_image.jpg" id="myImage" alt="Your Image" />

    const image = document.getElementById('myImage');

    image.onload = function() {
        EXIF.getData(image, function() {
            const allMetaData = EXIF.getAllTags(this);
            const dateTime = EXIF.getTag(this, "DateTimeOriginal");
            console.log(allMetaData);  // Logs all EXIF data
            console.log(dateTime);     // Logs the original date and time the photo was taken


Tables/Records/Columns v. Sets/Objects/Fields

These are similar concepts and in most cases we'd relate this using a mental spreadsheet paradigm as Tables & Rows. However, the Sets and Keys and Objects paradigm seems more in line with some of the data we're working with;

  • Objects with depth

  • Objects containing arrays

This becomes even more relevant as we add other types of data to the Datastore, which does not follow the CMS's table-like composition.

From a naming perspective


Objects can contain arrays. Therefore we need to be able to resolve a DSD to a selector type, i.e. Set ( keyed or unkeyed ), Object, or Field. or Invalid ( and in what way, for error logging )

Table / Set / Class / Collection

Record / Object / Tuple / Item

Column / Field / Attribute

Field types

Advanced ideas;

Stored Procs / Methods

PK FK AK Identity

Object paradigms; Inheritance, Methods, Base classes, Interfaces

Classes ( object definitons )

Attributes- use this to refer to META data regarding an item

Object Metadata

This is a feature we've wanted in Webflow's CMS for some time, and we may be able to add some of these features into SA5.

  • Image width, height, type, filesize

  • Video duration

  • Text length and word-count and language

Keyed v. Unkeyed Datasources

This distinction is currently under development. At present, only keyed sources are directly supported.

In a keyed datasource, you can retrieve a specific item by reference. In an unkeyed datasource, you can only perform list-wide operations.

Keyed DatasourceUn-keyed Datasource

Retrieve a specific object by key

Yes. E.g a CMS item slug


Retrieve object by position



Count items



Sort items



Bind to a list



Data Shapes

WFU utilizes primitive structural patterns which we refer to as data shapes;

  1. Table. A JSON array in which each element contains the same set of keys. Typically this is constructed from a tabular source such as a Webflow Collection List, or a CSV file.

  2. List. A Table with only one or two fields per element. Lists are primarily used for data-binding to FORM controls.

  3. Dictionary. A List, which has a key field and a value field. The key field content is expected to be unique. Dictionaries are used for lookups in template processing.

  4. Media.

Advanced DSNs

A DSN typically includes:

  • The name of the database driver (for example, PostgreSQL, MySQL, Oracle, etc.)

  • The hostname of the database server

  • The port number to connect to (if it's not the default port for the database)

  • The name of the database to connect to

  • The username and password for the database (though for security reasons, it's often best to supply these separately rather than including them in the DSN)

The exact format of a DSN can vary depending on the database driver. Here's an example of what a DSN might look like for a PostgreSQL database:

A DSN is typically used when setting up a database connection in an application. The DSN is given to the database driver or connection library, which parses the string and uses the information to establish a connection to the database.

Query Languages

SQL, GraphQL, XPath, etc.


Pre-defined named data views that include filtering and sorting constraints

Transform / Qualifier Suffixes

e.g. ? to indicate missing values = null


IF-THEN, for-each, loops...


Basic math in the form of evaluations




Relational Concepts

  1. Tables (Relations):

    • These are the primary data structures in an RDBMS.

    • A table consists of rows and columns where each row represents a record and each column represents an attribute or field of the record.

  2. Indexes:

    • These are data structures that improve the speed of data retrieval operations on a database table.

    • Common types of indexes include B-trees and hash indexes.

    • Indexes can be unique (enforcing the uniqueness of a value in a column) or non-unique.


    • A virtual table that represents the result of a stored query. Unlike tables, views don't store data; they display data from one or multiple tables through a specific query.

  4. Stored Procedures:

    • These are sets of SQL statements that can be stored in the database and executed as a single unit.

    • They can take parameters and return results.

  5. Triggers:

    • These are automatically executed (or fired) by the RDBMS in response to specific events on a particular table or view. Common events include insert, update, and delete operations.

  6. Cursors:

    • These are database objects used to traverse the records in a result set one by one and potentially make changes to the records.

  7. Constraints:

    • These are rules enforced on data columns of a table.

    • Examples include primary keys, foreign keys, unique constraints, and check constraints.

  8. System Catalog:

    • This is a collection of tables and views that contain metadata about the RDBMS, detailing all other objects in the database, their structure, and various attributes.

  9. Transaction Logs:

    • These are logs that keep a history of all transactions and changes in the database. They are crucial for ensuring data integrity and for recovery operations.

  10. Data Files:

  • Physical files on disk where the actual data from tables and other objects is stored.

  1. Control Files:

  • These are files that contain metadata about the physical structure of the database, including the database's creation date, the location of data files and redo log files, and the current log sequence number.

Last updated