Databricks vs Microsoft Fabric vs Snowflake
Same capabilities, same vocabulary, side by side. Where a source is recorded, each cell links to it.
| Capability | Databricks | Microsoft Fabric | Snowflake |
|---|---|---|---|
| Native support | 29 of 30 | 21 of 30 | 25 of 30 |
| Platform & Deployment | |||
| Cloud availabilityWhich public clouds can the platform run on? | Native AWS, Azure (Azure Databricks, a first-party Azure service) and Google Cloud. | Partial Runs on Azure only; OneLake shortcuts can reference data in AWS S3, Google Cloud Storage and others. | Native AWS, Azure and Google Cloud, in many regions; cross-cloud replication supported. |
| Deployment modelIs it SaaS, PaaS in the customer's cloud account, or self-managed? | Native Control plane run by Databricks; classic compute runs in the customer's cloud account, and serverless compute runs in Databricks' account. | Native Fully SaaS; no clusters or infrastructure in the customer's subscription. | Native Fully managed SaaS. |
| Pricing modelWhat unit is compute/storage billed in? | Native DBU-based. | Native Capacity-based (CU). | Native Credit-based compute, plus storage. |
| Storage & Formats | |||
| Open table formatsWhich open table formats (Delta Lake, Apache Iceberg) are supported natively? | Native Delta Lake native; Apache Iceberg supported through managed Iceberg tables and UniForm. Verify the current state. | Native Delta Lake (Parquet) is the native table format in OneLake; Iceberg interoperability is available. Verify its current status. | Native Native Snowflake table format plus Apache Iceberg tables (Snowflake-managed or externally managed catalog). |
| Storage/compute separationCan storage and compute scale independently? | Native | Native OneLake storage is decoupled from capacity compute. | Native A founding architectural principle (multi-cluster shared data). |
| Query external data in placeCan it query data in other clouds/storage without copying it? | Native Lakehouse Federation queries external databases; external locations reach cloud storage. | Native Shortcuts and mirroring bring external data into OneLake without traditional ETL. | Native External tables, Iceberg tables with external catalogs, external stages. |
| Compute & Workloads | |||
| SQL warehousingIs there a managed SQL engine for BI/analytical workloads? | Native | Native | Native |
| Serverless computeCan workloads run without the customer managing clusters? | Native Serverless SQL warehouses, notebooks, jobs and pipelines. | Native All compute is managed by the SaaS capacity model. | Native No clusters to manage; warehouses auto-suspend and auto-resume. Many serverless features exist (tasks, Snowpipe). |
| Spark & notebooksIs there managed Spark and a notebook experience? | Native Databricks was founded by the original creators of Apache Spark. | Native | Partial Snowflake Notebooks and Snowpark (DataFrame API) rather than managed Apache Spark; check the status of Spark-compatibility options. |
| LanguagesWhich languages can users write workloads in? | Native SQL, Python, Scala, R. | Native SQL (T-SQL), Python/PySpark, Scala, R, KQL, DAX. | Native SQL, Python, Java, Scala (via Snowpark), JavaScript (UDFs/procedures). |
| Integration & Pipelines | |||
| Managed ingestion connectorsAre there built-in connectors to ingest from SaaS apps and databases? | Native Lakeflow Connect managed connectors; Auto Loader for files. | Native | Native Snowpipe / Snowpipe Streaming, Openflow connectors. Verify Openflow status. |
| Declarative transformation pipelinesCan users define pipelines declaratively with managed dependencies and refresh? | Native Lakeflow Declarative Pipelines (formerly Delta Live Tables). | Unknown Dataflow Gen2 (Power Query) and materialized lake views. Assess how they compare with declarative pipelines elsewhere. | Native Dynamic Tables define transformations declaratively with target lag. |
| OrchestrationIs there built-in job/pipeline orchestration? | Native Lakeflow Jobs (formerly Databricks Workflows). | Native | Partial Tasks and task graphs; often paired with external orchestrators. |
| Streaming / real-timeCan it ingest and process streaming data with low latency? | Native Spark Structured Streaming; streaming tables in declarative pipelines. | Native | Native Snowpipe Streaming for low-latency ingestion. |
| Governance & Security | |||
| Unified catalogIs there a single catalog governing tables, files, models and other assets? | Native | Native OneLake catalog, with Microsoft Purview integration. | Native |
| LineageIs data lineage captured automatically? | Native Column-level lineage captured automatically in Unity Catalog. | Native Workspace lineage view; Purview for broader lineage. | Native Lineage in Snowsight (Horizon). Verify edition requirements. |
| Row/column-level securityAre row filters and column masking supported? | Native Row filters and column masks in Unity Catalog. | Unknown RLS/CLS exist in the warehouse and semantic models; OneLake security scope is evolving. Verify. | Native Row access policies and dynamic data masking (Enterprise edition or higher). |
| Sharing & Collaboration | |||
| Cross-organisation data sharingCan live data be shared with other organisations without copying? | Native Delta Sharing, an open protocol that also shares to non-Databricks consumers. | Partial External data sharing between Fabric tenants. Verify current scope. | Native Secure Data Sharing, with no data copied inside the same region; cross-region/cloud through replication. |
| Data marketplaceIs there a marketplace for third-party datasets and apps? | Native | Unknown | Native |
| Data clean roomsAre privacy-preserving clean rooms available? | Native | Unknown | Native |
| Analytics, ML & AI | |||
| Native BI / dashboardsDoes the platform include its own BI/dashboarding tool? | Native AI/BI Dashboards and Genie. | Native | Partial Snowsight dashboards and Streamlit in Snowflake; not a full BI suite, and usually paired with Tableau, Power BI, etc. |
| ML lifecycleAre experiment tracking, model registry and model serving built in? | Native Managed MLflow, Feature Store, Model Serving. | Partial MLflow-based experiments and models in Fabric Data Science; production model serving is typically done through Azure services. | Native Snowflake ML (Feature Store, Model Registry, model serving on Snowpark Container Services). |
| LLM functions in SQLCan LLM calls be made directly from SQL? | Native AI Functions (e.g. ai_query) callable from SQL. | Unknown AI functions exist for notebooks and dataframes. Verify SQL availability. | Native Cortex AI SQL functions. |
| Natural-language querying / data agentsCan business users ask questions in natural language over governed data? | Native AI/BI Genie spaces; Agent Bricks for building agents. | Native Copilot in Fabric and Fabric data agents. | Native Cortex Analyst and Snowflake Intelligence. Verify GA status. |
| Operational (OLTP) databaseIs there an operational database integrated with the analytics platform? | Partial Lakebase (managed Postgres). Verify GA status. | Partial SQL database in Fabric; check GA/preview status and other database options. | Partial Hybrid Tables (Unistore); Snowflake Postgres announced. Verify status. |
| Unification | |||
| Lifecycle coverageHow many of the ten planes does the platform answer with its own components? | Native Covers integration, data, metadata, quality, AI/ML and governance with its own components; visualisation is the thinnest, with dashboards rather than a full BI tool. | Native Answers integration, data, metadata, visualisation, AI/ML and much of governance with its own components - Data Factory, Lakehouse, Warehouse, Real-Time Intelligence, Power BI and Data Science. | Partial Strong on data, sharing, governance and AI, and adequate on integration; visualisation is limited to Snowsight rather than a full BI tool, and orchestration is thin. |
| Shared storageDoes one storage layer serve every engine, without copying data between them? | Native One lakehouse store on the customer's cloud object storage, read by every engine in open formats rather than copied per workload. | Native OneLake is included automatically in every tenant and is the single store for all analytics data. Microsoft's own wording is "one copy of data to use with multiple analytical engines without duplication", in Delta Parquet or Iceberg. | Native A single managed storage layer serves every workload, with Iceberg tables extending the same engine to data held outside Snowflake. |
| Shared governanceDoes one permission and policy model apply across every workload on the platform? | Native Unity Catalog "operates beneath every data and AI interaction" automatically, enforcing access control on a table query or a model call alike, and tracking lineage and audit across both. | Native Governance and security are built into OneLake itself rather than applied per engine, so policy follows the data across experiences. | Native One policy model across every workload, enforced by the engine itself at query time through masking and row access policies rather than documented and hoped for. Worth knowing when budgeting rather than when comparing architecture - masking, row access policies, classification, quality monitoring and lineage need Enterprise edition or higher. |
| Shared metadata and identityIs there one catalogue and one identity model spanning every workload, not one per service? | Native Unity Catalog is one catalogue across data and AI assets, enabled automatically for workspaces created after 8 November 2023; older workspaces need an upgrade. | Native One tenant-wide lake with a single catalogue across every workload; items are tenant objects rather than per-service resources. | Native One account-wide catalogue across workloads, reaching beyond Snowflake only through Snowflake-mediated paths such as Iceberg tables, the Iceberg REST catalog API and catalog-linked databases. |
| Sold as one platformIs it bought and billed as a single platform, rather than as separately licensed products? | Native One platform billed in DBUs across workloads rather than as separately licensed products. | Native Bought as Fabric capacity, with the experiences drawing on the same capacity rather than being licensed separately. | Native One platform billed in credits, though which features are available at all depends on the edition purchased. |
"Unknown" means not yet assessed, not "unsupported".