Snowflake Profiled

A fully managed cloud data platform with separate storage and compute, known for its SQL warehouse, live data sharing and marketplace.

At a glance

Snowflake is a fully managed SaaS data platform. It is best known for bringing cloud data warehousing into the mainstream with separate storage and compute. It has since added Python and ML (Snowpark, Snowflake ML), open formats (Apache Iceberg tables), ingestion (Snowpipe, Openflow) and GenAI (Cortex AI). Snowflake runs on AWS, Azure and Google Cloud.

Where it fits

  • Strongest when: SQL-centric analytics teams want near-zero administration, easy scaling for concurrency, and live data sharing with partners.
  • Consider carefully when: workloads centre on heavy Spark engineering, or data must stay entirely in open formats managed by other engines. Iceberg tables narrow this gap.

Key concepts

  • Organisation → Account → Database → Schema → Object
  • Virtual warehouses: compute sized T-shirt style (XS … 6XL), billed in credits per second
  • Editions: Standard, Enterprise, Business Critical and VPS; features such as masking policies depend on edition
  • Secure Data Sharing: consumers query the provider's data with no copy

Products (13)

Data Apps & Development

Data Engineering (Spark & Notebooks)

Notebooks in Snowsight for Python, SQL and Markdown, running on warehouses or container runtimes.

DataFrame APIs and runtimes for Python, Java and Scala that run inside Snowflake's compute.

Data Integration (ETL/ELT)

A managed data integration service, based on Apache NiFi, with connectors for structured and unstructured sources.

Data Science & ML

An end-to-end ML toolkit including Feature Store, Model Registry and model serving.

Data Sharing & Marketplace

Data Warehouse

Independently sized and scaled compute clusters that run SQL and Snowpark workloads against shared storage.

Generative AI & Agents

LLM functions, search and natural-language analytics running inside Snowflake's security boundary.

Governance & Catalog

Built-in governance for compliance, security, privacy, discovery and lineage across Snowflake objects.

Lakehouse

Tables in Apache Iceberg format stored in customer-owned cloud storage, managed by Snowflake or by an external catalog.

Transformation & Modelling

Declarative tables defined by a query and a target freshness (lag); Snowflake handles incremental refresh.

Upcoming events

From the blog

Capability snapshot

21 native · 4 partial

CapabilitySupportNotes
Platform & Deployment
Cloud availabilityNativeAWS, Azure and Google Cloud, in many regions; cross-cloud replication supported.
Deployment modelNativeFully managed SaaS.
Pricing modelNativeCredit-based compute, plus storage.
Storage & Formats
Open table formatsNativeNative Snowflake table format plus Apache Iceberg tables (Snowflake-managed or externally managed catalog).
Storage/compute separationNativeA founding architectural principle (multi-cluster shared data).
Query external data in placeNativeExternal tables, Iceberg tables with external catalogs, external stages.
Compute & Workloads
SQL warehousingNative
Serverless computeNativeNo clusters to manage; warehouses auto-suspend and auto-resume. Many serverless features exist (tasks, Snowpipe).
Spark & notebooksPartialSnowflake Notebooks and Snowpark (DataFrame API) rather than managed Apache Spark; check the status of Spark-compatibility options.
LanguagesNativeSQL, Python, Java, Scala (via Snowpark), JavaScript (UDFs/procedures).
Integration & Pipelines
Managed ingestion connectorsNativeSnowpipe / Snowpipe Streaming, Openflow connectors. Verify Openflow status.
Declarative transformation pipelinesNativeDynamic Tables define transformations declaratively with target lag.
OrchestrationPartialTasks and task graphs; often paired with external orchestrators.
Streaming / real-timeNativeSnowpipe Streaming for low-latency ingestion.
Governance & Security
Unified catalogNative
LineageNativeLineage in Snowsight (Horizon). Verify edition requirements.
Row/column-level securityNativeRow access policies and dynamic data masking (Enterprise edition or higher).
Sharing & Collaboration
Cross-organisation data sharingNativeSecure Data Sharing, with no data copied inside the same region; cross-region/cloud through replication.
Data marketplaceNative
Data clean roomsNative
Analytics, ML & AI
Native BI / dashboardsPartialSnowsight dashboards and Streamlit in Snowflake; not a full BI suite, and usually paired with Tableau, Power BI, etc.
ML lifecycleNativeSnowflake ML (Feature Store, Model Registry, model serving on Snowpark Container Services).
LLM functions in SQLNativeCortex AI SQL functions.
Natural-language querying / data agentsNativeCortex Analyst and Snowflake Intelligence. Verify GA status.
Operational (OLTP) databasePartialHybrid Tables (Unistore); Snowflake Postgres announced. Verify status.