Google Cloud Spanner integration
Google Cloud Spanner data, in your warehouse.
A built-in ingestr connector: add credentials, pick tables, schedule it.
name: raw.table
type: ingestr
parameters:
source_connection: google_cloud_spanner
source_table: '<table>'
destination: snowflake
incremental_strategy: merge$ bruin run assets/raw/google_cloud_spanner.asset.yml
- extract · Google Cloud Spanner dataincremental
- load · snowflake raw.datamerged
- checks · not_null, unique
Loaded and checked. Downstream models can run.
How it connects
Connected in three steps.
Google's globally distributed, horizontally scalable relational database service that combines the benefits of relational database structure with non-relational horizontal scale.
- 01
Add a Google Cloud Spanner connection with its credentials.
- 02
Pick the tables to load and how: replace, append or merge.
- 03
Bruin runs it on your schedule and checks every load.
Connection parameters
- project
- Google Cloud project ID
- instance
- Spanner instance ID
- database
- Spanner database name
- credentials_path
- Path to Google Cloud service account JSON file
Step-by-step
Pick a destination.
Google Cloud Spanner → Snowflake
Read the guide
Google Cloud Spanner → Google BigQuery
Read the guide
Google Cloud Spanner → Databricks
Read the guide
Google Cloud Spanner → Amazon Redshift
Read the guide
Google Cloud Spanner → PostgreSQL
Read the guide
Google Cloud Spanner → ClickHouse
Read the guide
Google Cloud Spanner → DuckDB
Read the guide
Google Cloud Spanner → MotherDuck
Read the guide
The platform
Part of the Bruin platform.
Data in, ready for everything downstream: the models, the checks, the lineage and the AI layer.
Sources
DatabasesWarehousesApps & APIsFiles & storageStreams & webhooksWeb scrapingMove
Data IngestionFrequently asked
Questions about Google Cloud Spanner.
Does Bruin have a built-in Google Cloud Spanner integration?
Yes. Built-in ingestr source.
Where can Google Cloud Spanner data go?
Snowflake, BigQuery, Databricks, Redshift, ClickHouse, Postgres, DuckDB, MotherDuck, Microsoft Fabric and more, plus files on S3 and GCS.
How fresh is the data?
As fresh as your schedule. Incremental loads append, merge or replace a time window, every few minutes if you like.
Do we need Bruin Cloud?
No. The Bruin CLI and ingestr run locally, in CI or in your own orchestrator. Bruin Cloud adds scheduling, lineage, alerts and the AI data analyst on top.
Ready to connect Google Cloud Spanner?
$100 in credits and 50 AI tasks. No credit card.
A demo walks through your own data.