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Concepts

This page outlines the key concepts of Datastores, providing a helpful foundation for learning how to set up and manage a Datastore.

Key-Value Pairs​

Data in a Datastore is represented with key-value pairs. A key is the name that corresponds to its matching value, and the value stores the actual data. For example, you may have a key named DOB that corresponds to a value that contains an employee's date of birth. When you need to access the date of birth of that employee you can reference the DOB key in Swarm and have the value of its key returned.

Tables​

Tables can be thought of as a database assigned to a key in your Datastore. A Table can now be created in place of uploading a CSV file, the table can be manually edited and created, or programmatically edited with a Swarm Flow.

Files​

Files can be imported and assigned to a Key in a Datastore. Supported file formats are below.

  • HTML
  • JavaScript
  • JSON
  • Markdown
  • Python

Modifying a Datastore with Flows​

Datastores can now be manipulated within a Swarm Flow. Flows can be used to update, delete and insert rows in a Datastore.

Data Retention​

Data is not automatically deleted when saved to the Datastore. When data is removed from the Datastore, it is permanently deleted and cannot be reconstructed or recovered.