Copy data
from DuckDB to Snowflake

Ingest data from DuckDB into Snowflake with no code required. Extend if needed with custom code.

Database

What is DuckDB?

DuckDB is an in-process SQL OLAP database management system designed to support fast analytical queries.

High Performance: Optimized for fast analytical queries, providing high performance for OLAP workloads.
In-Process Database: Runs within your application process, reducing latency and simplifying deployment.
Lightweight: Designed to be lightweight and easy to integrate into various environments.
SQL Support: Provides full SQL support, making it easy to query and analyze your data.

Data Warehouse

What is Snowflake?

Snowflake is a cloud-based data-warehousing platform that supports the big data and analytics.

Multiple Platforms: Snowflake supports various platforms, allowing seamless integration with AWS, Azure, GCP, and more.
Built on Cloud: Snowflake is a cloud-native data platform, offering flexibility and scalability without the need for dedicated infrastructure.
Secure Data Sharing: Snowflake provides secure and governed data sharing capabilities, enabling collaboration across your organization and with external partners.
Elastic Scalability: Snowflake's elastic scalability allows you to instantly scale up or down based on your workload demands, ensuring optimal performance and cost-efficiency.

Copy data between
DuckDB & Snowflake

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.