Google Cloud Storage connector

Set up the Google Cloud Storage connector in Kaivo: authentication, configuration, the BigQuery tables it syncs, and answers to common questions.

Written By Lauri Raivio

Last updated 1 day ago

Kaivo is a fully managed data platform that syncs your Google Cloud Storage data into a Google BigQuery warehouse and keeps it up to date automatically. There is no pipeline to build and no infrastructure to run, so you can spend your time analysing your data from Google Cloud Storage instead of moving it.

What is the Google Cloud Storage connector

Sync CSV, JSON, and Excel files from your Google Cloud Storage buckets into BigQuery with Kaivo, with no manual uploads or custom scripts.

CategoryFiles & Databases, Tech
AuthenticationAPI key
SetupSelf-service

Getting started with the Google Cloud Storage connector

  1. Sign up for Kaivo and create a workspace.
  2. Connect your Google Cloud Storage account.
  3. Choose which tables to sync.
  4. Wait for the initial sync to finish.
  5. Query your data in BigQuery or your favourite AI or BI tool.

Authenticating Google Cloud Storage

Authenticate with your Google Cloud Storage credentials. You provide:

FieldDescription
Bucket

The name of the bucket to read from.

Service Account Key

The contents of a JSON key file for a service account that has the "Storage Object Viewer" role on the bucket.

Configuring the Google Cloud Storage connector

When you set up the connector, you provide:

FieldDescription
Name

A name to identify the tables parsed from the file(s).

Paths

One or more paths inside the bucket, such as exports/*.csv. Use ** to match across directories. Multiple files are combined together and should follow the same schema.

Delimiter

A one-character string used to separate fields. If no value is given, auto-detection is used instead. An explicit value is recommended for reliability.

Quote Character

A one-character string used to quote fields containing special characters.

Escape Character

A one-character string used to remove any special meaning from the following character.

Text Encoding

File character encoding, such as utf-8 or latin-1. Defaults to utf-8-sig, which allows an optional BOM (byte order marker).

JSON Path Prefix

A path inside the JSON structure, in which the data items can be found. Path components must be separated by periods. Use "item" to indicate an array item.

Multiple JSON Values

Allow multiple top-level JSON values. Required for NDJSON (Newline-Delimited JSON) or JSONL (JSON Lines) files.

Comments

Allow C-style // ... and /* ... */ comments. Required for JSONC (JSON with Comments) files.

Tables and columns synced from Google Cloud Storage

The available streams and columns mirror the tables and fields in your own database, so they are determined when the connection runs rather than listed here.

How the Google Cloud Storage sync works

After the first load, Kaivo keeps your BigQuery warehouse up to date for you. Where Google Cloud Storage supports it, each sync pulls only new and changed records so it stays fast; otherwise it refreshes the whole table. Every record keeps its original ID, so you won't get duplicate rows.

Frequently asked questions

How long does the initial sync take for Google Cloud Storage?

It depends on how much history is in your Google Cloud Storage account. Most initial syncs finish within minutes, while large accounts can take a few hours. After that, syncs only fetch new and changed records, so they're much faster.

Can I sync only some tables or columns?

Yes. You pick which tables to sync when you set up the connection and can change the selection later. Tables you don't select are never copied to your warehouse.

What happens when Google Cloud Storage's schema changes?

New fields are never added automatically. You choose which fields to sync, so data you haven't selected (sensitive personal data, for example) never lands in your warehouse. When a new field appears, it becomes available for you to add. What happens to removed or renamed fields depends on a table's sync mode: full-refresh tables always match what's currently in Google Cloud Storage, so dropped fields disappear, while incremental tables keep their existing columns and history, so an old field stays and newly added fields fill in over time.

How do I handle GDPR or data deletion requests?

Your data lives in your own Kaivo-managed BigQuery warehouse, so the most direct option is to delete or anonymise specific records right in BigQuery. If you delete data in Google Cloud Storage instead, full-refresh tables drop it on the next sync, while incremental tables keep it, so you would remove the row in BigQuery or ask us to run a full refresh. To remove everything, delete the Google Cloud Storage connector in Kaivo and all of its synced data is deleted with it.

Common use cases for Google Cloud Storage data

Load flat files

Turn files a team already drops in a bucket into queryable BigQuery tables on a schedule.

Recurring exports

Pick up scheduled exports from systems that have no API but can write to storage.

Combine with app data

Join file data with your CRM or finance tables in BigQuery instead of in a spreadsheet.

Use Google Cloud Storage data in your AI and BI tools

Once Google Cloud Storage data lands in your Kaivo-managed BigQuery warehouse, you can explore it with AI tools or any BI tool that connects to BigQuery. Here's how the most common destinations work with Google Cloud Storage data.

Claude

Use Kaivo's MCP server to give Claude secure, workspace-scoped access to your data. Setup guide →

Power BI

Microsoft's BI tool with a native BigQuery connector. Supports direct query and scheduled refresh. Setup guide →

Data Studio

Free Google BI tool with native BigQuery support. One-click connection to your Kaivo warehouse; great for SMB teams on Google Workspace. Setup guide →

Tableau

The premium analytics standard, with native BigQuery integration. Setup guide →

Google Sheets

Use Connected Sheets to query BigQuery directly from a spreadsheet, with no SQL. Setup guide →

Excel

Connect via Power Query's BigQuery connector. Setup guide →

Metabase

Open-source BI tool with strong BigQuery support. Setup guide →

See our pricing page for Google Cloud Storage connector pricing and plan details.