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Snowflake

~2m skim, 404 words, updated Sep 28, 2025

A modern data engineering platform.

Contents

Why Snowflake?¶

• Fully managed: no hardware or server provisioning required
• Compute / storage decoupled
• Auto-scaling, auto-suspend, etc.
• Support for semi-structured data (JSON, VARIANT, etc.)
• Zero-copy cloning, time travel, data sharing
• Strong ecosystem and connector support

Key Concepts & Architecture¶

• Snowsight UI (web interface)
• SnowSQL (CLI)
• Notebooks (Snowflake Notebooks)
• Architecture: hybrid of shared-disk and shared-nothing. Central storage + multiple MPP compute clusters.
• Snowflake Documentation
• Cloud Platforms: Runs on AWS, Azure, GCP.
• Snowflake Documentation
• Micro-partitions (internal detail)
• Compute / Storage separation
• Zero-copy cloning, Time Travel, Fail-safe

Editions & Pricing¶

• Editions: Standard, Enterprise, Business Critical, Virtual Private Snowflake (VPS)
• Pricing model: credits for compute + storage + usage
• How edition differences affect features (e.g. multi-cluster, data protection)

Core Objects & DDL¶

• Databases, Schemas, Tables, Views
• External Tables, Streams, Tasks
• Sequences, Stages
• Examples of CREATE / ALTER / DROP
• Cloning & object versioning

Data Ingestion / Loading¶

• Stages: internal (user, table, named) vs external cloud stages
• Snowflake Documentation
• COPY INTO / bulk load
• Snowpipe (continuous ingestion)
• Snowflake Documentation
• Snowpipe Streaming
• Loading semi-structured data and schema inference

Querying & DML¶

• SELECT, INSERT, UPDATE, DELETE, MERGE
• Joins, subqueries, functions
• Working with semi-structured data (VARIANT, OBJECT, ARRAY)
• Window functions, CTEs, analytic SQL

Warehouses & Compute¶

• What is a warehouse; required for queries / DML
• Snowflake Documentation
• Warehouse sizes and billing
• Snowflake Documentation
• Auto-suspend, auto-resume
• Multi-cluster warehouses
• Best practices for compute sizing & concurrency

Performance & Cost Optimization¶

• Choosing warehouse sizes vs concurrency
• Pruning / clustering / clustering keys
• Caching, result caching
• Query profiling / query history
• Avoiding overprovisioning / idle compute

Security & Access Control¶

• Roles, users, grants, privileges
• Snowflake Documentation
• Object-level permissions
• Row access policies, masking policies
• Network / IP policies, secure views, encryption

Integration & Connectors¶

• JDBC, ODBC, Python connector
• Spark / Snowflake connector
• Kafka Connector
• BI tools (Tableau, Power BI, etc.)
• Data marketplace & data sharing

Snowpark (Python, Java, Scala APIs)¶

Advanced Features¶

• Time Travel & Fail-safe
• Zero-copy cloning
• Materialized Views
• Tasks & scheduled pipelines
• Search optimization service
• Streams & Change Data Capture (CDC)

Tips, Best Practices & Gotchas¶

• Avoid leaving warehouses running unnecessarily
• For small queries, very large warehouses may not help
• Use clustering only when needed
• Be aware of billing granularity (per second)
• Watch out for too many small files in load
• Query patterns that can disrupt performance

References & Further Reading¶

• Official Snowflake documentation (docs.snowflake.com)
• Snowflake Documentation
• Tutorials (“Snowflake in 20 minutes”)
• Snowflake Documentation
• Quickstarts & hands-on labs
• Snowflake Quickstarts
• SQL command reference
• Snowflake Documentation