Uploaded June 2026 | Updated September 2026, 3 weeks ago
First Databricks introduced Genie Spaces, then Genie Code. Here's the difference.
→ Genie Spaces sits where business questions get asked. Chat, dashboards, reporting. No SQL required.
→ Genie Code sits where the engineering happens. Notebooks, pipelines, dashboard authoring, MLflow.
The detail worth knowing if you're rolling this out to a team: both run on the same Unity Catalog governance layer. An analyst's chart in Genie Spaces and a data scientist's notebook in Genie Code are pulling from the same governed source of truth, not two separate systems with their own rules.
Save this for the next time someone asks which Databricks assistant they should be using.
First Databricks introduced Genie Spaces, then Genie Code. Here's the difference.
→ Genie Spaces sits where business questions get asked. Chat, dashboards, reporting. No SQL required.
→ Genie Code sits where the engineering happens. Notebooks, pipelines, dashboard authoring, MLflow.
The detail worth knowing if you're rolling this out to a team: both run on the same Unity Catalog governance layer. An analyst's chart in Genie Spaces and a data scientist's notebook in Genie Code are pulling from the same governed source of truth, not two separate systems with their own rules.
Save this for the next time someone asks which Databricks assistant they should be using.





![DAIWT Paris 2025: Replay Keynote
[Keynote en anglais] David Meyer, VP Produits chez Databricks, présente la Data Intelligence Platform: une plateforme unifiée qui simplifie le développement et le déploiement d’agents IA grâce à Unity Catalog pour la gouvernance des données et de l’IA, et une stack ouverte intégrée. La plateforme inclut LakeFlow (ETL), DBSQL (data warehousing) et le nouveau Lakehouse transactionnel, pour offrir l’analytics avancé et l’IA à tous les utilisateurs.
Chapitres:
00:06 : Introduction : l’IA et le problème des silos
03:21 : Le concept Lakehouse et la gouvernance unifiée
06:14 : Agent Bricks : simplifier les agents IA
08:18 : La Data Intelligence Platform
10:45 : Témoignage client : Flow Health
19:15 : LakeFlow : moteur ETL principal
25:02 : DBSQL : l’entrepôt de données
29:57 : Lakebase : base de données dans le lakehouse
35:20 : Applications Databricks et AI/BI
41:24 : Conclusion DAIWT Paris 2025: Replay Keynote](https://i.ytimg.com/vi/yyQ8ck6ff7w/mqdefault.jpg)



