Integration · Data warehouse
Delta Lake + OrchestrAI
Catalog exported 2026-09-02 · Delta Lake website
Create, optimize, and vacuum Delta Lake tables from chat through your Spark connection.
OrchestrAI exposes 8 Delta Lake operations: 2 are low-risk (read-only or low-impact), and 6 create or modify resources and run only after you confirm the plan. 4 of them also carry a step-level approval gate.
What teams use it for
Lakehouse teams ask OrchestrAI to compact a Delta table after a heavy ingest and to vacuum files older than the retention window once they are sure no reader needs them. Creating a table waits for confirmation, optimize runs on request, and vacuum is rated high because it permanently removes files, so it is confirmed before running. These operations run through the connected Spark credential rather than a Databricks token. There is no operation for time travel queries, schema changes, or reading table history, so use Spark SQL for those.
Every Delta Lake operation, with its risk level
| Operation | What it does | Risk | Step-level approval |
|---|---|---|---|
Get Spark Application Status |
Get Spark application status | Low risk | No |
List Spark Applications |
List running Spark applications | Low risk | No |
Create Delta Table |
Create Delta Lake table | Creates resources | Yes |
Create Iceberg Table |
Create Apache Iceberg table | Creates resources | Yes |
Kill Spark Application |
Kill Spark application | Creates resources | Yes |
Optimize Delta Table |
Optimize Delta Lake table | Creates resources | No |
Submit Spark Job |
Submit Spark job via spark-submit | Creates resources | No |
Vacuum Delta Table |
Vacuum Delta Lake table to remove old files | Modifies existing | Yes |
Risk tiers come from the catalog: low is read-only or low-impact, medium creates resources and is reversible, high modifies existing resources, destructive may lose data. Every plan that creates or changes resources is shown with its cost estimate and waits for your confirmation. Operations marked with a step-level approval pause again on their own step. Destructive operations require a typed risk phrase.
What you connect
A Delta Lake credential (stored as spark).
Connected-service tokens are envelope-encrypted with a per-record key wrapped by a cloud KMS.
Prompts that work
- Optimize the Delta table gold.daily_revenue
- Vacuum the bronze.events Delta table with a 168 hour retention
- Create a Delta Lake table called silver.customers at s3://lake/silver/customers with columns id, email, created_at
Before anything runs
Every mutation shows its plan, cost estimate, and blast radius, then waits for your confirmation. Destructive operations require a typed risk phrase. Credentials are minted per run through OIDC federation and discarded afterward; nothing you create here is invisible later, because every resource lands in the desired-state ledger where drift is detected and can be converged. Details on the security page.
Frequently asked questions
- Is vacuuming a Delta Lake table through OrchestrAI reversible?
- No, and that is why it is rated high risk. Vacuum deletes files no longer referenced by the table, so OrchestrAI waits for confirmation before running it.
- Do I need Databricks to use the Delta Lake operations?
- No. The Delta Lake operations use a Spark credential, so they work against any Spark environment with Delta support.
- How does OrchestrAI authenticate to Delta Lake?
- You add a Delta Lake credential once in the connections screen. It is envelope-encrypted with a per-record key wrapped by a cloud KMS and is only decrypted inside the run that needs it.
Related integrations
Try it on your own account
Connect your cloud read-only and see your resources, drift, and costs before anything runs. $5 minimum to start. Unused credits refunded in your first 14 days.
Unused credits refunded in your first 14 days.