Google BigLake API

Name: BigLake API
Brand: BigLake API
Availability: InStock

✓ Official Vendor SpecStorageDatabaseoauth210 EndpointsREST

Install Jentic One Beta

Connect the BigLake API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the BigLake API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with BigLake API.

Create and list catalogs in BigLake Metastore at /v1/{+parent}/catalogs

Create and list databases inside a catalog via /v1/{+parent}/databases

Create, get, patch, and delete Iceberg table entries scoped to a database

GET STARTED

Start building with BigLake API

Explore with Jentic

View OpenAPI Document

For Agents

Manage Apache Iceberg catalogs, databases, and tables in Google Cloud BigLake Metastore for open-source data lakes.

Use for: I need to create an Iceberg catalog in BigLake Metastore, List every database in a catalog and their table counts, Rename an Iceberg table without dropping and recreating it, Patch a table's labels for cost-tracking purposes

Not supported: Does not run queries, store table data, or transform records - use for managing BigLake Metastore catalogs, databases, and Iceberg table metadata only.

The BigLake API provides programmatic access to BigLake Metastore, a serverless metastore for open-source data formats - primarily Apache Iceberg tables - that can be queried from BigQuery and Spark. It exposes operations to manage catalogs, databases, and tables, including a rename operation for schema evolution. Resources are scoped to a project and location, and the metastore makes the same data discoverable to multiple compute engines without per-engine setup. The API does not run queries or process data; it manages metadata only.

Use Cases

Patterns agents use BigLake API for, with concrete tasks.

★ Iceberg-Based Data Lake on Google Cloud

Run an open Iceberg-format data lake on Cloud Storage and make the tables queryable from BigQuery and Spark by registering them in BigLake Metastore. The API is the single integration surface for catalog and database management, so onboarding a new domain is a matter of creating a catalog plus the relevant databases and tables.

POST a catalog create request to /v1/{parent}/catalogs and then create the underlying databases for each domain.

Schema Evolution Without Data Movement

Rename Iceberg tables and databases as schemas evolve without copying data. The dedicated rename endpoint updates the metastore reference, leaving the underlying object-storage data in place and avoiding rewrite cost. Useful during refactors that consolidate or split domains.

POST a new name to /v1/{name}:rename for the source resource and verify the response.

Cross-Engine Data Discovery

Make the same Iceberg datasets discoverable to BigQuery, Dataproc Spark, and external Iceberg-aware engines from one metastore. The API exposes list endpoints suitable for building a data catalog UI or feeding lineage tools without parsing object-storage layouts.

List all catalogs and their databases, and feed the results into a downstream data catalog tool as a metadata sync.

AI Agent Data Lake Hygiene via Jentic

Use an AI agent to keep BigLake catalogs tidy by listing resources, identifying stale entries, and renaming or deleting them on a schedule. Through Jentic the agent finds the rename and delete operations by intent and runs them with project credentials supplied at execute time, removing the need for SDK setup in the agent.

Use Jentic search for 'rename a table in BigLake Metastore', load the schema for /v1/{name}:rename, and execute it with the new name.

Key Endpoints

10 endpoints — the biglake api provides programmatic access to biglake metastore, a serverless metastore for open-source data formats - primarily apache iceberg tables - that can be queried from bigquery and spark.

METHOD

PATH

DESCRIPTION

GET

/v1/{+name}

Get a catalog, database, or table by resource name

PATCH

/v1/{+name}

Update a database or table's mutable fields

DELETE

/v1/{+name}

Delete a catalog, database, or table

POST

/v1/{+name}:rename

Rename a metastore resource

GET

/v1/{+parent}/catalogs

List catalogs in a project and location

POST

/v1/{+parent}/catalogs

Create a catalog

GET

/v1/{+parent}/databases

List databases in a catalog

POST

/v1/{+parent}/databases

Create a database

GET

/v1/{+name}

Get a catalog, database, or table by resource name

PATCH

/v1/{+name}

Update a database or table's mutable fields

DELETE

/v1/{+name}

Delete a catalog, database, or table

POST

/v1/{+name}:rename

Rename a metastore resource

GET

/v1/{+parent}/catalogs

List catalogs in a project and location

Why Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

Your Google Cloud OAuth credential is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'create a BigLake catalog' or 'rename an Iceberg table', and Jentic returns the matching operation with its input schema so the agent calls the right endpoint without reading the full reference.

Time to first call

FAQs

Specific to using BigLake API through Jentic.

What authentication does the BigLake API use?

The API uses Google OAuth 2.0 with cloud-platform scope. Service accounts must hold the roles/biglake.* IAM role on the project. Through Jentic the service account credential is encrypted in the vault and only short-lived access tokens reach the agent.

Can I rename an Iceberg table through the BigLake API?

Yes. POST a new name to /v1/{name}:rename on the table, database, or catalog resource. Renaming updates the metastore reference without moving the underlying object-storage data.

How do I create a new catalog through Jentic?

Search Jentic for 'create a BigLake catalog'. Jentic returns POST /v1/{parent}/catalogs with the input schema; execute it with the catalog name and Jentic supplies the credential from the vault. The catalog is then ready for databases.

What are the rate limits for the BigLake API?

Numeric limits are not declared in the spec; quotas are enforced per project on biglake.googleapis.com. Review the project's quota dashboard before driving large numbers of metadata changes.

Does BigLake run queries against the data?

No. BigLake is a metastore. Queries run in BigQuery, Dataproc Spark, or another Iceberg-aware engine pointed at the same metastore. This API exposes only the metadata surface.

Can I list catalogs across multiple projects in one call?

No. The list endpoint is scoped to a parent in the form projects/{project}/locations/{location}. Iterate the projects you care about and call the list endpoint for each.

Google BigLake API

Connect the BigLake API to your agent

Capabilities

Start building with BigLake API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs