Snowflake IDENTITY & AUTOINCREMENT: How To Use Identity Columns in Snowflake

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May 2, 2024

Managing unique identifiers in database tables is crucial for data integrity and analysis. Snowflake provides a robust mechanism for creating unique IDs for each row inserted into a table through identity columns. This tutorial will guide you through the process of adding and utilizing identity columns in Snowflake, covering key features such as Identity Resolution and RampID Translation.

What is an Identity Column in Snowflake?

Identity columns in Snowflake are used to automatically generate unique identifiers for new rows in a table. These columns rely on Snowflake's internal sequence to produce values, which may not always be consecutive but are guaranteed to be unique. Unlike sequence objects that can be shared across tables, identity properties are specific to each table. This tutorial will explore how to add identity columns to your Snowflake tables and leverage Snowflake's identity features for data management.

Example of creating a table with an identity column

CREATE TABLE employees (
name STRING,

This SQL statement creates a new table named 'employees' with an identity column 'id' that automatically generates unique IDs for each new row.

How To Add An Identity Column Using AUTOINCREMENT Or IDENTITY

To add an identity column to an existing table in Snowflake, you can use the AUTOINCREMENT or IDENTITY keyword as a default value for a column. This approach is straightforward and ensures that each new row receives a unique identifier.

Example of altering a table to add an identity column


This code snippet demonstrates how to alter an existing 'employees' table to include an 'id' column with auto-incrementing values.

2. Creating a New Table with an Identity Column

If you need to add an identity column to a table that already contains data, you can create a new table with the same structure as the existing one and include an identity column. Afterward, you can migrate the data from the old table to the new one.

Example of creating a new table with an identity column and migrating data

CREATE TABLE new_employees LIKE employees;
INSERT INTO new_employees (name, role) SELECT name, role FROM employees;

This example shows how to create a new table with an identity column and migrate existing data without losing any information.

Common Challenges and Solutions

Working with identity columns in Snowflake can present several challenges, especially regarding the non-sequential nature of generated IDs and the management of identity properties.

  • Non-Sequential IDs: Snowflake's use of cached sequence values for batch inserts means that IDs may not be sequential. While this behavior supports performance and scalability, it may require adjustment in applications expecting consecutive numbers.
  • Identity Property Limitations: Since identity properties are tied to specific tables, they cannot be reused across multiple tables. Consider using sequence objects for scenarios requiring shared sequences.
  • Data Migration: When adding an identity column to an existing table with data, careful planning is needed to ensure data integrity during migration to a new table with the identity column.

Best Practices for Using Identity Columns in Snowflake

Effectively utilizing identity columns in Snowflake involves understanding their behavior and limitations. Here are some best practices to follow:

  • Plan for Non-Sequential IDs: Design your applications and data models to accommodate the possibility of non-sequential IDs generated by Snowflake.
  • Use Sequences for Shared Identifiers: For scenarios requiring identifiers to be shared across tables, consider using sequence objects instead of identity columns.
  • Test Data Migration Strategies: Before migrating data to a new table with an identity column, thoroughly test your migration strategy to prevent data loss or corruption.

Further Learning on Snowflake Identity Features

To deepen your understanding of Snowflake's identity capabilities, consider exploring the following topics:

  • Identity Resolution: Learn how Snowflake enables the stitching together of customer data from across your business into cohesive profiles within the Data Cloud.
  • RampID Translation: Dive into how Snowflake translates pseudonymous identifiers for cross-party use, enhancing data collaboration and privacy.
  • Delimited Identifiers: Understand the flexibility Snowflake offers in naming identifiers, including the use of special characters and spaces.

Recap of Implementing Identity Columns in Snowflake

This tutorial covered the essentials of adding and utilizing identity columns in Snowflake, including methods for adding identity columns, understanding identity features, and best practices for managing unique identifiers. By applying these concepts, you can enhance data integrity and management within your Snowflake environment.

  • Identity columns provide a mechanism for generating unique row identifiers in Snowflake tables.
  • Understand the limitations and behaviors of identity columns, including non-sequential ID generation.
  • Explore advanced identity features like Identity Resolution and RampID Translation to leverage Snowflake's full capabilities.

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