Iceberg tables¶

An Iceberg table uses the Apache Iceberg open table format specification, which provides an abstraction layer on data files stored in open formats and supports features such as:

ACID (atomicity, consistency, isolation, durability) transactions
Schema evolution
Hidden partitioning
Table snapshots

Iceberg tables for Snowflake combine the performance and query semantics of regular Snowflake tables with external cloud storage that you manage. They are ideal for existing data lakes that you cannot, or choose not to, store in Snowflake.

Snowflake supports Iceberg tables that use the Apache Parquet file format.

Getting started¶

To get started with Iceberg tables, see Tutorial: Create your first Iceberg table.

How Iceberg tables work¶

This section provides information specific to working with Iceberg tables in Snowflake. To learn more about the Iceberg table format specification, see the official Apache Iceberg documentation and the Iceberg Table Spec.

Data storage
Iceberg catalog
Metadata and snapshots
Cross-cloud/cross-region support
Billing

Data storage¶

Iceberg tables store their data and metadata files in an external cloud storage location (Amazon S3, Google Cloud Storage, or Azure Storage). The external storage is not part of Snowflake. You are responsible for all management of the external cloud storage location, including the configuration of data protection and recovery. Snowflake does not provide Fail-safe storage for Iceberg tables.

Snowflake connects to your storage location using an external volume, and Iceberg tables incur no Snowflake storage costs. For more information, see Billing.

To learn more about storage for Iceberg tables, see Iceberg table storage.

External volume¶

An external volume is a named, account-level Snowflake object that you use to connect Snowflake to your external cloud storage for Iceberg tables. An external volume stores an identity and access management (IAM) entity for your storage location. Snowflake uses the IAM entity to securely connect to your storage for accessing table data, Iceberg metadata, and manifest files that store the table schema, partitions, and other metadata.

A single external volume can support one or more Iceberg tables.

To set up an external volume for Iceberg tables, see Configure an external volume for Iceberg tables.

Iceberg catalog¶

An Iceberg catalog enables a compute engine to manage and load Iceberg tables. The catalog forms the first architectural layer in the Iceberg table specification and must support:

Storing the current metadata pointer for one or more Iceberg tables. A metadata pointer maps a table name to the location of that table’s current metadata file.
Performing atomic operations so that you can update the current metadata pointer for a table.

To learn more about Iceberg catalogs, see the Apache Iceberg documentation.

Snowflake supports different catalog options. For example, you can use Snowflake as the Iceberg catalog, or use a catalog integration to connect Snowflake to an external Iceberg catalog.

Catalog integration¶

A catalog integration is a named, account-level Snowflake object that stores information about how your table metadata is organized when you don’t use Snowflake as the Iceberg catalog. For example, you need a catalog integration if your table is managed by AWS Glue.

A single catalog integration can support one or more Iceberg tables that use the same external catalog.

To set up a catalog integration, see Configure a catalog integration for Iceberg tables.

Metadata and snapshots¶

Iceberg uses a snapshot-based querying model, where data files are mapped using manifest and metadata files. A snapshot represents the state of a table at a point in time and is used to access the complete set of data files in the table.

To learn about table metadata and Time Travel support, see Metadata and retention.

Cross-cloud/cross-region support¶

Cross-cloud/cross-region support depends on the type of Iceberg table.

Table type	Cross-cloud/cross-region support	Notes
Tables that use a catalog integration	✔	If the active storage location for your external volume is not with the same cloud provider or in the same region as your Snowflake account, the following limitations apply: You can’t use the SYSTEM$GET_ICEBERG_TABLE_INFORMATION function to retrieve information about the latest refreshed snapshot. You can’t convert the table to use Snowflake as the catalog. If your Snowflake account and external volume are in different regions, your external cloud storage account incurs egress costs when you query the table.
Tables that use Snowflake as the catalog	❌	Your external volume must use an active storage location with the same cloud provider (in the same region) that hosts your Snowflake account. If the active location is not in the same region, the CREATE ICEBERG TABLE statement returns a user error.

Table type

Cross-cloud/cross-region support

Notes

Tables that use a catalog integration

✔

If the active storage location for your external volume is not with the same cloud provider or in the same region as your Snowflake account, the following limitations apply:

You can’t use the SYSTEM$GET_ICEBERG_TABLE_INFORMATION function to retrieve information about the latest refreshed snapshot.
You can’t convert the table to use Snowflake as the catalog.

If your Snowflake account and external volume are in different regions, your external cloud storage account incurs egress costs when you query the table.

Tables that use Snowflake as the catalog

❌

Your external volume must use an active storage location with the same cloud provider (in the same region) that hosts your Snowflake account.

If the active location is not in the same region, the CREATE ICEBERG TABLE statement returns a user error.

Billing¶

Snowflake bills your account for virtual warehouse (compute) usage and cloud services when you work with Iceberg tables.

Snowflake does not bill your account for the following:

Iceberg table storage costs. Your cloud storage provider bills you directly for data storage usage.
Active bytes used by Iceberg tables. However, the INFORMATION_SCHEMA.TABLE_STORAGE_METRICS and ACCOUNT_USAGE.TABLE_STORAGE_METRICS views display ACTIVE_BYTES for Iceberg tables to help you track how much storage a table occupies. To view an example, see Retrieve storage metrics for Iceberg tables.

Note

If your Snowflake account and external volume are in different regions, your external cloud storage account incurs egress costs when you query the table.

Iceberg catalog options¶

When you create an Iceberg table in Snowflake, you can use Snowflake as the Iceberg catalog or you can use a catalog integration to connect to an external Iceberg catalog.

The following table summarizes the differences between these catalog options.

	Use Snowflake as the Iceberg catalog	Use an external catalog
Read access	✔	✔
Write access	✔	❌ For Snowflake platform support, you can convert the table to use Snowflake as the catalog.
Data and metadata storage	External volume (cloud storage)	External volume (cloud storage)
Snowflake platform support	✔	❌
Works with the Snowflake Iceberg Catalog SDK	✔	✔

Use Snowflake as the Iceberg catalog¶

An Iceberg table that uses Snowflake as the Iceberg catalog provides full Snowflake platform support with read and write access. The table data and metadata are stored in external cloud storage, which Snowflake accesses using an external volume. Snowflake handles all life-cycle maintenance, such as compaction, for the table.

Use an external catalog¶

An Iceberg table that uses an external catalog provides limited Snowflake platform support with read-only access. With this table type, Snowflake uses a catalog integration to retrieve information about your Iceberg metadata and schema.

You can use this option to create an Iceberg table registered in the AWS Glue Data Catalog or to create a table from Iceberg metadata files in object storage.

Snowflake does not assume any life-cycle management on the table.

The table data and metadata are stored in external cloud storage, which Snowflake accesses using an external volume.

The following diagram shows how an Iceberg table uses a catalog integration with an external Iceberg catalog.

How Iceberg tables that use a catalog integration work

Considerations and limitations¶

The following considerations and limitations apply to Iceberg tables, and are subject to change:

Clouds and regions

Iceberg tables are available for all Snowflake accounts, on all cloud platforms and in all regions except for SnowGov Regions.

Cross-cloud/cross-region tables are supported when you use an external catalog. For more information, see Cross-cloud/cross-region support.

Iceberg

Versions 1 and 2 of the Apache Iceberg specification are supported, excluding the following features:

Row-level deletes (either position deletes or equality deletes). However, tables that use Snowflake as the catalog support Snowflake DELETE statements.

Using the history.expire.min-snapshots-to-keep table property to specify the default minimum number of snapshots to keep. For more information, see Metadata and snapshots.

Iceberg partitioning with the bucket transform function impacts performance for queries that use conditional clauses to filter results.

For Iceberg tables that aren’t managed by Snowflake, be aware of the following:

Time travel to any snapshot generated after table creation is supported as long as you periodically refresh the table before the snapshot expires.

Converting a table that has an un-materialized identity partition column isn’t supported. An un-materialized identity partition column is created when a table defines an identity transform using a source column that doesn’t exist in a Parquet file.

File formats

Iceberg tables support Apache Parquet files.

Parquet files that use the unsigned integer logical type aren’t supported.

External volumes

You can’t access the cloud storage locations in external volumes using a storage integration.

You must configure a separate trust relationship for each external volume that you create.

Metadata files

The metadata files don’t identify the most recent snapshot of an Iceberg table.

You can’t modify the location of the data files or snapshot using the ALTER ICEBERG TABLE command. To modify either of these settings, you must recreate the table (using the CREATE OR REPLACE ICEBERG TABLE syntax).

For tables that use an external catalog:

Ensure that manifest files don’t contain duplicates. If duplicate files are present in the same snapshot, Snowflake returns an error that includes the path of the duplicate file.

You can’t create a table if the Parquet metadata contains invalid UTF-8 characters. Ensure that your Parquet metadata is UTF-8 compliant.

Snowflake detects corruptions and inconsistencies in Parquet metadata produced outside of Snowflake, and surfaces issues through error messages.

It’s possible to create, refresh, or query externally managed (or converted) tables, even if the table metadata is inconsistent. When writing Iceberg data, ensure that the table’s metadata statistics (for example, RowCount or NullCount) match the data content.

For tables that use Snowflake as the catalog, Snowflake processes DDL statements individually and produces metadata in a way that might differ from other catalogs. For more information, see DDL statements.

Clustering

Clustering support depends on the type of Iceberg table.

Table type

Notes

Tables that use Snowflake as the Iceberg catalog

Set a clustering key by using either the CREATE ICEBERG TABLE or the ALTER ICEBERG TABLE command. To set or manage a clustering key, see CREATE ICEBERG TABLE (Snowflake as the Iceberg catalog) and ALTER ICEBERG TABLE.

Tables that use an external catalog

Clustering is not supported.

Converted tables

Snowflake only clusters files if they were created after converting the table, or if the files have since been modified using a DML statement.

Table type	Notes
Tables that use Snowflake as the Iceberg catalog	Set a clustering key by using either the CREATE ICEBERG TABLE or the ALTER ICEBERG TABLE command. To set or manage a clustering key, see CREATE ICEBERG TABLE (Snowflake as the Iceberg catalog) and ALTER ICEBERG TABLE.
Tables that use an external catalog	Clustering is not supported.
Converted tables	Snowflake only clusters files if they were created after converting the table, or if the files have since been modified using a DML statement.

Access by third-party clients to Iceberg data, metadata

Third-party clients can’t append to, delete from, or upsert data to Iceberg tables that use Snowflake as the catalog.

Unsupported features

The following Snowflake features aren’t currently supported:

Cloning. Clones of databases and schemas don’t include Iceberg tables.

The following drivers:

ODBC Driver

.NET Driver

PHP PDO Driver for Snowflake

Node.js Driver

Fail-safe

Hybrid tables

Listings that enable Cross-Cloud Auto-Fulfillment.

Query Acceleration Service

Replication of Iceberg tables, external volumes, or catalog integrations

Search optimization service

Snowflake encryption

Snowflake Native App Framework

Snowflake schema evolution

Snowpipe Streaming:

Snowflake Connector for Kafka Connector with Snowpipe Streaming

Snowflake Ingest SDK

Snowpipe Streaming API

Tagging using the ASSOCIATE_SEMANTIC_CATEGORY_TAGS stored procedure

Temporary and transient tables

Additionally, the following features aren’t supported for Iceberg tables that use an external catalog:

Clustering

Standard and append-only streams. Insert-only streams are supported.