Guides - Snowflake Documentation

Connecting to Snowflake

Snowflake provides a variety of mechanisms for connecting to Snowflake and executing database commands. Choose between the web interface or the command line tool to connect to your Snowflake account. Learn how to use connectors to integrate third-party data into Snowflake.

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Web Interface

Snowsight distills Snowflake’s powerful SQL support into a unified, easy-to-use experience. Use Snowsight to perform your critical Snowflake operations.

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Command Line

Detailed instructions for installing, configuring, and using the Snowflake command-line client, snowsql.

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Connectors

The Snowflake Connectors provide native integration of third-party applications and database systems in Snowflake. The connectors provide instant access to current data without the need to manually integrate against API endpoints.

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Snowflake Fundamentals

Learn the basics of warehouses, tables, and views in Snowflake.

Snowflake Warehouses

Learn how to set up and use virtual data warehouses to process the SQL statements that you execute.

Overview of Warehouses

Multi-cluster Warehouses

Warehouse Considerations

Working with Warehouses

Using the Query Acceleration Service

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Basics of Snowflake Tables and Views

Learn how to design and create tables and views for your data.

Understanding Snowflake Table Structures

Table Design Considerations

Overview of Views

Working with Secure Views

Cloning Considerations

Table Storage Considerations

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Basics of Data Types

Learn about Snowflake data types and their uses

Introduction to Snowflake Data Types

Numeric Data Types

String and Binary Data Types

Logical Data Types

Date & Time Data Types

Geospatial Data Types

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Getting data in to Snowflake

Snowflake provides several different methods to load data in to Snowflake, such as by using Snowpipe, loading from cloud storage, or uploading files using Snowsight.

Working with data

Queries and other standard database features are just the beginning when you work with your data in Snowflake. You also use machine learning functions to analyze data in Snowflake.

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Queries

Snowflake supports standard SQL, including a subset of ANSI SQL:1999 and the SQL:2003 analytic extensions. Learn how to use queries to interact with Snowflake using simple queries, joins, and more.

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Views, Materialized Views, & Dynamic Tables

Views are just the beginning of how you can examine data. Snowflake provides a number of mechanism for joining data including Materialized Views and Dynamic Tables.

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Streams and Tasks

Streams and tasks make executing complex task based solutions simple and easy. Streams allow you to track changes to database objects and tasks provide a mechanism to then execute SQL when those events occur.

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ML Functions

ML Functions are Snowflake’s intelligent, fully-managed service that enables organizations to quickly analyze data within Snowflake.

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Collaborating

Share data and applications with other Snowflake users. Discover and publish listings of data products on the Snowflake Marketplace, share data products privately, or use a direct share to quickly share data with someone in the same region.