Unnest in Snowflake — Examples & 2025 Guide

Handling nested data is a common scenario in cloud data platforms like Snowflake — JSON arrays, objects, and complex columns are everywhere. Unnesting lets you expand arrays or objects into rows, making your data easier to analyze, join, and transform. But writing unnest queries in Snowflake can be challenging, especially if you’re more comfortable with spreadsheets or BI tools.

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What Is UNNEST in Snowflake and Why Does It Matter?

Snowflake doesn’t have a literal UNNEST function like some databases (BigQuery, Postgres), but it provides similar functionality using FLATTEN. Whether you’re processing event logs, user actions, or any JSON arrays, flattening (unnesting) is the secret to making nested data usable for analytics and reporting.

• Business analysts can extract individual purchases, clicks, or events from nested columns.

• Data engineers can join and aggregate individual elements for advanced transformations.

• Anyone can remove coding friction using AI2sql to write, debug, and optimize unnest (flatten) queries.

How to Unnest (Flatten) in Snowflake

1. Identify the column to expand (typical for ARRAY or OBJECT types).

2. Use the FLATTEN table function in the FROM clause to produce one row per element.

3. Optionally, join unnested elements back to their source row or other tables.

Real-World Examples — UNNEST (FLATTEN) in Snowflake

Example 1: Unnesting a Simple ARRAY Column

SELECT user_id, f.value AS product_id
FROM purchases,
     LATERAL FLATTEN(input => purchases.product_ids) f;

Example 2: Extracting Nested JSON Fields

SELECT event_id, f.value:action::STRING AS action
FROM events,
     LATERAL FLATTEN(input => events.json_data:actions) f;

Example 3: Join Flattened Data to Parent Table

SELECT o.order_id, i.value:sku::STRING AS sku, i.value:qty::INT AS quantity
FROM orders o,
     LATERAL FLATTEN(input => o.items) i;

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Mini-Benchmark Table: Performance Unnesting in Snowflake

Best Practices and Troubleshooting

• Always alias the flatten output (commonly f or i) and reference value for the unnested value.

• Use JOIN or LATERAL to connect unnested elements with other table columns.

• Cast values out of VARIANT format as needed for analytics (::STRING, ::INT).

• Let AI2sql auto-generate the perfect FLATTEN query from your prompt.

Further Learning

• Try AI2sql Unnest Generator

• Unnest in Snowflake Tutorial

• Unnest in Snowflake Examples

• Explore the AI2sql platform

Conclusion

Unnesting (flattening) is a foundational skill for working with nested or JSON data in Snowflake, enabling richer insights and more flexible reporting. Manual SQL can be tricky, but with AI2sql you can skip the documentation, reduce errors, and save hours — just type what you want, and get results instantly. Fast, scalable, and trusted by 50 000+ developers and analysts worldwide.

Try AI2sql’s Snowflake unnest generator today.