# Use Iceberg Topics with GCP Lakehouse > For the complete documentation index, see [llms.txt](https://docs.redpanda.com/llms.txt). Component-specific: [cloud-data-platform-full.txt](https://docs.redpanda.com/cloud-data-platform-full.txt) --- title: Use Iceberg Topics with GCP Lakehouse latest-operator-version: v26.2.1 latest-console-tag: v3.10.0 latest-connect-version: 4.105.0 latest-redpanda-tag: v26.2.1 docname: iceberg/iceberg-topics-gcp-biglake page-component-name: cloud-data-platform page-version: master page-component-version: master page-component-title: Cloud page-relative-src-path: iceberg/iceberg-topics-gcp-biglake.adoc page-edit-url: https://github.com/redpanda-data/cloud-docs/edit/main/modules/manage/pages/iceberg/iceberg-topics-gcp-biglake.adoc description: Add Redpanda topics as Iceberg tables to Google Lakehouse for Apache Iceberg that you can query from Google BigQuery. page-git-created-date: "2026-06-11" page-git-modified-date: "2026-06-11" --- > 💡 **TIP** > > This guide is for integrating Iceberg topics with a managed REST catalog. Integrating with a REST catalog is recommended for production deployments. If it is not possible to use a REST catalog, you can use the [filesystem-based catalog](https://docs.redpanda.com/cloud-data-platform/manage/iceberg/use-iceberg-catalogs/#object-storage). For an example of using the filesystem-based catalog to access Iceberg topics, see the [Getting Started with Iceberg Topics on Redpanda BYOC](https://www.redpanda.com/blog/iceberg-topics-redpanda-cloud-byoc-setup) blog post. This guide walks you through querying Redpanda topics as Iceberg tables stored in Google Cloud Storage, using a REST catalog integration with [Google Lakehouse for Apache Iceberg](https://docs.cloud.google.com/lakehouse/docs/introduction) (formerly BigLake). After completing this guide, you will be able to: - Create a catalog in GCP Lakehouse for Iceberg topic data. - Configure a Redpanda cluster to use GCP Lakehouse as an Iceberg REST catalog. - Query Iceberg topic data from Google BigQuery. For general information about Iceberg catalog integrations in Redpanda, see [Use Iceberg Catalogs](https://docs.redpanda.com/cloud-data-platform/manage/iceberg/use-iceberg-catalogs/). > 📝 **NOTE** > > Check the [Lakehouse product page](https://docs.cloud.google.com/lakehouse/docs) for the latest status and availability of the REST Catalog API. ## [](#prerequisites)Prerequisites - A Google Cloud Platform (GCP) project. - Lakehouse must be in the same GCP project as the cluster. Cross-project Lakehouse is not supported. If you do not have permissions to manage GCP resources such as VMs, storage buckets, and service accounts in your project, ask your project owner to create or update them for you. - The [`gcloud` CLI](https://docs.cloud.google.com/sdk/docs/install) installed and configured for your GCP project. - [Lakehouse (BigLake) API](https://cloud.google.com/biglake/docs/enable-biglake-api) enabled for your GCP project. - Redpanda version 25.3 or later. - `rpk` [installed or updated](https://docs.redpanda.com/cloud-data-platform/manage/rpk/rpk-install/) to the latest version. - You can also use the Redpanda Cloud API to [reference secrets in your cluster configuration](https://docs.redpanda.com/cloud-data-platform/manage/cluster-maintenance/config-cluster/#set-cluster-configuration-properties). > 📝 **NOTE** > > For BYOC clusters created before June 9, 2026, you must re-run `rpk cloud byoc gcp apply --redpanda-id= --project-id=` to enable the required API services before following this guide. This is a one-time operation. ## [](#limitations)Limitations ### [](#multi-region-bucket-support)Multi-region bucket support The Lakehouse runtime catalog does not support multi-region buckets. Use single-region buckets to store your Iceberg topics. ### [](#catalog-deletion)Catalog deletion Currently, it is not possible to delete non-empty Lakehouse Iceberg catalogs through the Lakehouse interface. If you need to reconfigure your setup, create a new bucket or use the REST API to remove the existing catalog. ### [](#topic-names)Topic names Lakehouse does not support Iceberg table names that contain dots (`.`). When creating Iceberg topics in Redpanda that you plan to access through Lakehouse, either: - Use the `iceberg_topic_name_dot_replacement` cluster property to set a replacement string for dots in topic names. Ensure that the replacement value does not cause table name collisions. For example, `current.orders` and `current_orders` would both map to the same table name if you set the replacement to an underscore (`_`). - Ensure that the new topic names do not include dots. You must also set the `iceberg_dlq_table_suffix` property to a value that does not include dots or tildes (`~`). See [Configure Redpanda for Iceberg](#configure-redpanda-for-iceberg) for the list of cluster properties to set when enabling the Lakehouse REST catalog integration. ## [](#set-up-google-cloud-resources)Set up Google Cloud resources For BYOC clusters, the required Lakehouse IAM permissions are automatically provisioned and attached to the cluster’s service account when Iceberg is enabled with a Lakehouse endpoint. You can skip to [Create a Lakehouse catalog](#create-a-lakehouse-catalog). For BYOVPC clusters, you must grant the required permissions to your cluster’s service account and enable the `biglake.googleapis.com` and `bigquery.googleapis.com` APIs in your GCP project. ### [](#grant-required-permissions)Grant required permissions Grant the necessary permissions to your service account. To run the following commands, replace the placeholder values: - ``: The name of your service account. - ``: The name of your storage bucket. 1. Grant the service account the [Storage Object Admin role](https://docs.cloud.google.com/storage/docs/access-control/iam-roles) to access the bucket: ```bash gcloud storage buckets add-iam-policy-binding gs:// \ --member="serviceAccount:@$(gcloud config get-value project).iam.gserviceaccount.com" \ --role="roles/storage.objectAdmin" ``` 2. Grant [Service Usage Consumer](https://docs.cloud.google.com/iam/docs/roles-permissions/serviceusage) and [BigLake Editor](https://docs.cloud.google.com/iam/docs/roles-permissions/biglake#biglake.editor) roles for using the Iceberg REST catalog: ```bash gcloud projects add-iam-policy-binding $(gcloud config get-value project) \ --member="serviceAccount:@$(gcloud config get-value project).iam.gserviceaccount.com" \ --role="roles/serviceusage.serviceUsageConsumer" gcloud projects add-iam-policy-binding $(gcloud config get-value project) \ --member="serviceAccount:@$(gcloud config get-value project).iam.gserviceaccount.com" \ --role="roles/biglake.editor" ``` ### [](#create-a-lakehouse-catalog)Create a Lakehouse catalog Create a Lakehouse Iceberg REST catalog using the [`gcloud biglake`](https://docs.cloud.google.com/sdk/gcloud/reference/biglake/iceberg/catalogs/create) command: ```bash gcloud biglake iceberg catalogs create --catalog-type=gcs-bucket --project= ``` Replace the placeholder values: - ``: Use the name of your storage bucket as the catalog ID. - ``: Your GCP project ID. ## [](#configure-redpanda-for-iceberg)Configure Redpanda for Iceberg 1. Edit your cluster configuration to set the `iceberg_enabled` property to `true`, and set the catalog integration properties listed in the example below. Use `rpk` as shown in the following example, or [use the Cloud API](https://docs.redpanda.com/cloud-data-platform/manage/cluster-maintenance/config-cluster/#set-cluster-configuration-properties) to update these cluster properties. The update might take several minutes to complete. ```bash rpk cloud login rpk profile create --from-cloud rpk cluster config set \ iceberg_enabled=true \ iceberg_catalog_type=rest \ iceberg_rest_catalog_endpoint=https://biglake.googleapis.com/iceberg/v1/restcatalog \ iceberg_rest_catalog_authentication_mode=gcp \ iceberg_rest_catalog_warehouse=gs:/// \ iceberg_rest_catalog_gcp_user_project= \ iceberg_dlq_table_suffix=_dlq ``` - ``: Your Redpanda cluster ID. - ``: For BYOC clusters, the bucket name is `redpanda-cloud-storage-`. For BYOVPC clusters, use the name of the object storage bucket you created as a customer-managed resource. - ``: Your GCP project ID. - You must set the `iceberg_dlq_table_suffix` property to a value that does not include dots or tildes (`~`). The example above uses `_dlq` as the suffix for the [dead-letter queue (DLQ) table](https://docs.redpanda.com/cloud-data-platform/manage/iceberg/iceberg-troubleshooting/#dead-letter-queue). 2. Enable the REST catalog integration for a topic by configuring the topic property `redpanda.iceberg.mode`. The following examples show how to use [`rpk`](https://docs.redpanda.com/cloud-data-platform/manage/rpk/rpk-install/) to either create a new topic or alter the configuration for an existing topic and set the Iceberg mode to `key_value`. The `key_value` mode creates a two-column Iceberg table for the topic, with one column for the record metadata including the key, and another binary column for the record’s value. See [Specify Iceberg Schema](https://docs.redpanda.com/cloud-data-platform/manage/iceberg/specify-iceberg-schema/) for more details on Iceberg modes. Create a new topic and set `redpanda.iceberg.mode`: ```bash rpk topic create --topic-config=redpanda.iceberg.mode=key_value ``` Set `redpanda.iceberg.mode` for an existing topic: ```bash rpk topic alter-config --set redpanda.iceberg.mode=key_value ``` Iceberg data can take a few moments to become available in Lakehouse. ## [](#query-iceberg-topics-in-bigquery)Query Iceberg topics in BigQuery 1. Navigate to the [BigQuery console](https://console.cloud.google.com/bigquery). 2. Query your Iceberg topic using SQL. For example, to query the `transactions` topic in the quickstart cluster: ```sql SELECT * FROM `>redpanda`.transactions ORDER BY redpanda.timestamp DESC LIMIT 10 ``` Replace `` with your bucket name. Your Redpanda topic is now available as Iceberg tables in Lakehouse, allowing you to run analytics queries directly on your streaming data. ### [](#manage-access-for-query-engine-users)Manage access for query engine users Redpanda manages the permissions between Redpanda and the BigLake catalog. To grant your end users and query engines read access to the Iceberg tables in BigQuery, see [Grant permissions for BigLake tables](https://cloud.google.com/bigquery/docs/manage-open-source-metadata#grant_permissions) in the Google Cloud documentation. ## [](#suggested-reading)Suggested reading - [Use Iceberg Catalogs](https://docs.redpanda.com/cloud-data-platform/manage/iceberg/use-iceberg-catalogs/) - [Query Iceberg Topics](https://docs.redpanda.com/cloud-data-platform/manage/iceberg/query-iceberg-topics/) - [Google Lakehouse for Apache Iceberg documentation](https://docs.cloud.google.com/lakehouse/docs/introduction)