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GitHub - datafuselabs/databend: ๐——๐—ฎ๐˜๐—ฎ, ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ & ๐—”๐—œ. Modern alternative to Snowflake. Cost-effective and simple for massive-scale analytics. https://databend.com
๐——๐—ฎ๐˜๐—ฎ, ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ & ๐—”๐—œ. Modern alternative to Snowflake. Cost-effective and simple for massive-scale analytics. https://databend.com - datafuselabs/databend
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GitHub - datafuselabs/databend: ๐——๐—ฎ๐˜๐—ฎ, ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ & ๐—”๐—œ. Modern alternative to Snowflake. Cost-effective and simple for massive-scale analytics. https://databend.com

GitHub - datafuselabs/databend: ๐——๐—ฎ๐˜๐—ฎ, ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ & ๐—”๐—œ. Modern alternative to Snowflake. Cost-effective and simple for massive-scale analytics. https://databend.com

๐Ÿ‹ Introduction

Databend, built in Rust, is an open-source cloud data warehouse that serves as a cost-effective alternative to Snowflake. With its focus on fast query execution and data ingestion, it's designed for complex analysis of the world's largest datasets.

โšก Performance

TPC-H Benchmark: Databend Cloud vs. Snowflake

Databend vs. Snowflake

Data Ingestion Benchmark: Databend Cloud vs. Snowflake

Databend vs. Snowflake

๐Ÿš€ Why Databend

  • Cloud-Native: Integrates with AWS S3, Azure Blob, Google Cloud, and more.

  • High Performance: Rust-built, with cutting-edge, high-speed vectorized execution. ๐Ÿ‘‰ ClickBench.

  • Cost-Effective: Designed for scalable storage and computation, reducing costs while enhancing performance. ๐Ÿ‘‰ TPC-H.

  • AI-Powered Analytics: Enables advanced analytics with AI Functions.

  • Data Simplification: Streamlines data ingestion, no external ETL needed. ๐Ÿ‘‰ Data Loading.

  • Real-Time CDC: Supports real-time incremental data updates to keep data current and accurate. ๐Ÿ‘‰ Stream

  • Format Flexibility: Supports multiple data formats and types, including JSON, CSV, Parquet, GEO, and more.

  • ACID Transactions: Ensures data integrity with atomic, consistent, isolated, and durable operations.

  • Version Control: Provides Git-like version control for data, allowing querying, cloning, and reverting at any point.

  • Schemaless: VARIANT data type enabling schemaless data storage and flexible data modeling.

  • Flexible Indexing: Virtual Column, Aggregating Index, and Full-Text Index, for faster data retrieval.

  • Community-Driven: Join a welcoming community for a user-friendly cloud analytics experience.

๐Ÿ“ Architecture

Databend Architecture

๐Ÿš€ Try Databend

1. Databend Serverless Cloud

The fastest way to try Databend, Databend Cloud

2. Install Databend from Docker

Prepare the image (once) from Docker Hub (this will download about 170 MB data):

docker pull datafuselabs/databend

To run Databend quickly:

docker run --net=host  datafuselabs/databend

๐Ÿš€ Getting Started

๐Ÿค Contributing

Databend thrives on community contributions! Whether it's through ideas, code, or documentation, every effort helps in enhancing our project. As a token of our appreciation, once your code is merged, your name will be eternally preserved in the system.contributors table.

Here are some resources to help you get started:

๐Ÿ‘ฅ Community

For guidance on using Databend, we recommend starting with the official documentation. If you need further assistance, explore the following community channels:

๐Ÿ›ฃ๏ธ Roadmap

Stay updated with Databend's development journey. Here are our roadmap milestones:

๐Ÿ“œ License

Databend is released under a combination of two licenses: the Apache License 2.0 and the Elastic License 2.0.

When contributing to Databend, you can find the relevant license header in each file.

For more information, see the LICENSE file and Licensing FAQs.

๐Ÿ™ Acknowledgement

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