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.

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.