Databend Products

Welcome to the Databend (pronounced as /ˈdeɪtəˌbɛnd/) documentation.

Databend is an open-source, serverless, cloud-native data lakehouse built on object storage with a decoupled storage and compute architecture. It delivers exceptional performance and rapid elasticity, aiming to be the open-source alternative to Snowflake.

Introduction to Databend Products

Check out the products you can choose from.

Databend Cloud

Fully-Managed on Cloud

Databend Enterprise

Self-Hosted with Additional Enterprise Features

Databend Community

Self-Hosted & Free

Getting Started

Create a Databend Cloud account or deploy your own Databend instance.

Activate Databend Cloud

This topic outlines the steps for applying for beta access as an organization.

Topics you might find useful:

• Supported Platforms & Regions
• Databend Cloud Editions
• Pricing & Billing

Self-Hosted Databend

This topic provide detailed instructions for deploying and upgrading Databend.

Topics you might find useful:

• Downloading Databend
• Licensing Databend
• Upgrading Databend

Connect to Databend

Connect your application to Databend in just a few minutes.

Developer Resources →

BendSQL

Java

Golang

Python

Node.js

Rust

Load Data into Databend

Bulk import data into Databend(Cloud) in multiple formats.

Know More →

Kafka

dbt

Airbyte

Flink CDC

Addax

DataX

Debezium

Tapdata

Vector

AI & BI & Visualization & Notebooks

Databend offers connectors and plugins for integrating with major data import tools, ensuring efficient data synchronization.

All Tools →

Deepnote

Jupyter

Metabase

Grafana

Redash

Superset

Tableau

MindsDB

Continuous Data Pipelines

Data pipelines automate the process of moving and changing data from different sources into Databend.

Know More →

Real-Time CDC Ingestion

Automated Data Pipelines

Additional Information

AI Capabilities

Security

Contact Support

Use Cases

FAQ

Changelog

Product Features

Serverless Elastic Architecture

Stateless compute nodes with serverless elasticity enable rapid scaling and recovery based on workload.

Object Storage & HDFS

Stores all data in object storage to reduce costs, while supporting HDFS for existing Hadoop and Hive clusters.

Parquet Data Format

Uses the standard Parquet format, eliminating data lock-in risks.

Decoupled Storage and Compute

Designed for multi-tenant data sharing with a truly decoupled architecture, enabling data marketplace functionality.

Open Source with Flexible Deployment

Supports both public cloud SaaS and private deployments, with an open-source core to avoid vendor lock-in.

Data Lake Support

Reads data from Iceberg, Hive, and Delta Lake seamlessly.

Here are some entries you might want to learn about

• SQL Reference: your swift-access guide for Databend essentials!
• Data Unloading: Export data from Databend(Cloud).
• External Functions: Use external functions to extend Databend's capabilities.
• Data Management: Manage data in Databend(Cloud).
• Benchmarks: Compare Databend Cloud performance with Snowflake on TPC-H SF100 benchmarks.
• Accessing Data Lake: Databend presents a seamless integration with three robust Data Lake technologies—Apache Hive, Apache Iceberg, and Delta Lake.
• Query Structures: Databend supports diverse query structures to enhance your data querying experience
• Performance Optimization: Databend supports the following features to optimize query performance across various scenarios