SQL-only BI shops (Snowflake or BigQuery simpler), Iceberg-purist buyers wary of Databricks owning Delta Lake, or small teams without dedicated data engineering.
Mid-market and enterprise data teams (200-50,000 employees) running serious ML training plus analytics, where lakehouse governance and AI workflow integration matter more than pure SQL simplicity.
Why we say this
Editorial pulled these weaknesses from Databricks Lakehouse Platform’s product card in our Top 10 Data Lakehouse Software for 2026:
- ! DBU pricing complexity, plus separate cloud infra costs charged by hyperscaler
- ! Delta vs Iceberg neutrality is contested given Databricks owns Delta Lake project
- ! Unity Catalog migration painful for legacy Hive metastore customers
If Databricks Lakehouse Platform is wrong for you, consider these instead
Same Data Lakehouse category, different best-fit buyer.
Best for
Engineering-led teams (100-5,000 employees) committing to Iceberg lakehouse architecture who want to separate storage from compute vendor and use a query engine outside the Databricks/Snowflake duopoly.
See full profile →Best for
Organizations standardized on Databricks or Microsoft Fabric where Delta is the path of least resistance, with Delta UniForm available for occasional Iceberg interop.
See full profile →Best for
GCP-anchored organizations (any size) wanting lakehouse semantics on Iceberg/Hudi/Delta with BigQuery as the primary engine, plus tight Looker and Vertex AI integration.
See full profile →Related editorial
Last updated 2026-05-27. Editorial verdict based on the published Top 10 Data Lakehouse Software for 2026 ranking. Disagree? Tell us.