Copy data
from Google Sheets to Databricks

Ingest data from Google Sheets into Databricks with no code required. Extend if needed with custom code.

Spreadsheet Software

What is Google Sheets?

Google Sheets is a web-based spreadsheet application that allows you to create, edit, and collaborate on spreadsheets online.

Real-Time Collaboration
Work simultaneously with others on the same spreadsheet with real-time updates.
Functionality
Includes a wide range of functions and formulas for data analysis and manipulation.
Integration with Google Apps
Seamlessly integrates with other Google Workspace apps such as Google Docs and Google Drive.
Add-Ons and Extensions
Supports a variety of add-ons and extensions to enhance functionality.

Data Analytics Platform

What is Databricks?

Databricks is a unified data analytics platform that accelerates innovation by unifying data engineering, data science, and business analytics.

Unified Data Platform
Combines data engineering, data science, and business analytics in a single platform.
Collaborative Environment
Provides collaborative notebooks and integrated workflows to enhance team productivity.
Scalable and Flexible
Scales seamlessly with your data and workload demands, ensuring optimal performance and cost-efficiency.
Advanced Analytics and ML
Built-in support for machine learning and advanced analytics, allowing for powerful data insights.

Copy data between
Google Sheets & Databricks

Bruin Cloud enables you to copy data between any source and destination.

App screenshot

Build data pipelines faster

Built-in connectors, defined with YAML

Bruin is a code-based platform, meaning that everything you do comes from a Git repo, versioned. All of the data ingestions are defined in code, version controlled in your repo.

Multiple platforms
Bruin supports quite a few platforms as built-in connectors. You can ingest data from AWS, Azure, GCP, Snowflake, Notion, and more.
Built on open-source
Bruin's ingestion engine is built on ingestr, an open-source data ingestion tool.
Custom sources & destinations
Bruin supports pure Python executions, enabling you to build your own data ingestion code.
Incremental loading
Bruin supports incremental loading, meaning that you can ingest only the new data, not the entire dataset every time.

Build safer

End-to-end quality in raw data

Bruin's built-in data quality capabilities are designed to ensure that the data you ingest is of the highest quality and always matches with your expectations.

Built-in quality checks
Bruin supports built-in quality checks, such as not_null, accepted_values, and more, all ready to be used in all assets.
Custom quality checks
Bruin allows you to define custom quality checks in SQL, enabling you to define your own quality standards.
Templating in quality checks
Bruin supports templating in quality checks, meaning that you can use variables in your checks, and run checks only for incremental periods.
Automated alerting
Failing quality checks will automatically send alerts to the configured channels, ensuring that you are always aware of the data quality issues.