Google Cloud Listing
Google's cloud data stack, built around BigQuery with BigLake for open storage, Knowledge Catalog for context and governance, Looker for BI and Vertex AI for machine learning.
Capability snapshot
10 native · 2 partial
| Capability | Support | Notes |
|---|---|---|
| Compute & Workloads | ||
| SQL warehousing | Native | BigQuery is a serverless managed SQL engine for analytical workloads, and is the centre the rest of the stack is arranged around. |
| Spark & notebooks | Native | Managed Spark on clusters or serverless, plus notebooks through Colab Enterprise and Vertex AI Workbench. Note the rename - Managed Service for Apache Spark now covers what were Dataproc on Compute Engine and Google Cloud Serverless for Apache Spark. |
| Languages | Native | GoogleSQL in BigQuery, Python through BigQuery DataFrames and notebooks, and Spark on Managed Service for Apache Spark covering Python, Scala, Java and R. SQL, Python and R are all first-class. |
| Governance & Security | ||
| Row/column-level security | Native | Row-level security and column-level policy tags in BigQuery, enforced by the engine. Worth checking against your contract rather than your architecture - Google notes row-level security may be unavailable on reservations created with certain BigQuery editions. |
| Analytics, ML & AI | ||
| Native BI / dashboards | Native | Looker for governed enterprise BI on a semantic model, with Looker Studio for lighter self-service. Licensed separately from BigQuery, which is part of why the platform scores only partial on being sold as one thing. |
| ML lifecycle | Native | Vertex AI, now documented under Gemini Enterprise Agent Platform, provides experiment tracking, a Model Registry and managed serving endpoints, with notebooks through Colab Enterprise and Workbench. |
| Operational (OLTP) database | Native | Several first-party operational databases - AlloyDB, Spanner and Cloud SQL - and BigQuery reaches them directly. Federated queries send a statement to any of the three through the BigQuery Connection API and return the result as a temporary table, using EXTERNAL_QUERY. |
| Unification | ||
| Lifecycle coverage | Native | Covers the lifecycle end to end with its own components - Dataflow and Datastream for integration, BigQuery and BigLake for storage and analytics, Knowledge Catalog for metadata and governance, Looker for BI, Vertex AI for machine learning. |
| Shared storage | Native | Apache Iceberg managed tables, formerly BigLake tables for Apache Iceberg in BigQuery, give the same fully managed experience as standard BigQuery tables while storing data in customer-owned buckets, and Google states they let open-source and third-party engines work from a single copy of data. BigLake also reaches Amazon S3 and Azure Blob Storage. Worth knowing that this is a table-type choice rather than the default, since standard BigQuery storage remains its own format. |
| Shared governance | Native | IAM is one identity and permission model across the whole cloud, which is a reach few competitors match since it covers every service rather than one vendor's workspace. Knowledge Catalog carries governance across the estate on top of it. Mechanisms differ by service - BigQuery column and row policies are not object-level IAM on Cloud Storage - but that is true of every platform here, and the model is one. |
| Shared metadata and identity | Partial | Knowledge Catalog provides universal business context across the estate through a context graph, and was renamed from Dataplex Universal Catalog on 10 April 2026 with API, CLI and IAM names unchanged. It sits over more than one technical catalogue rather than replacing them, though - BigQuery holds its own metadata, and Dataproc Metastore is a separate fully managed Hive metastore for lake and Hive workloads. One context layer, several catalogues underneath. |
| Sold as one platform | Partial | One account and one bill, but the components are separately metered products and Looker is licensed separately again. Closer to a well-integrated portfolio than a single platform purchase. |