Databend Products
Welcome to the Databend (pronounced as /ˈdeɪtəˌbɛnd/) documentation.
Databend — ANY DATA. ANY SCALE. ONE DATABASE.
Open-source datastore, vector, analytics, search, and geospatial engines converge on one Snowflake-compatible SQL surface so teams store anything, search everything, power semantic workloads, and deliver real-time insights without moving data.
Explore the engine on GitHub. Launch in Databend Cloud, docker run, or pip install databend—every option runs the same unified engine on your object store.
Introduction to Databend Products
Choose the deployment option that best fits your needs and scale.
Product Features
Unified Engine
Analytics, vector, search, and geo share one optimizer and runtime.
Unified Data
Structured, semi-structured, unstructured, and vector data share object storage.
Analytics Native
ANSI SQL, windowing, incremental aggregates, and streaming power BI.
Vector Native
Embeddings, vector indexes, and semantic retrieval all run in SQL.
Search & Geo Native
JSON inverted indexes, geo functions, and ranking fuel hybrid maps.
Unified Deployment
Databend runs the same in Cloud, Docker, or `pip install`.
Getting Started
Create a Databend Cloud account or deploy your own Databend instance.
AI & BI & Visualization & Notebooks
Databend offers connectors and plugins for integrating with major data import tools, ensuring efficient data synchronization.
All Tools →Continuous Data Pipelines
Data pipelines automate the process of moving and changing data from different sources into Databend.
Know More →Additional Information
Here are some entries you might want to learn about
Getting Started
- Quick Start: Launch Databend with Docker and load sample data fast.
- Databend Cloud: Spin up serverless warehouses and manage your organization.
- Connect to Databend: Connect with various SQL clients and programming languages.
- SQL Reference: Browse Databend SQL commands, functions, and syntax.
Data Processing
- Data Loading: Import data from various sources into Databend.
- Data Unloading: Export data from Databend to different formats.
- Semi-Structured Data: Process JSON, arrays, and nested data with VARIANT type.
Unified Workloads
- SQL Analytics Guide: Shared session tables for analytics, search, vector, and geo workloads.
- JSON & Search Guide: Query VARIANT payloads with inverted indexes and Lucene-style
QUERY. - Vector Database Guide: Store embeddings and run semantic similarity inside Databend.
- Geo Analytics Guide: Map incidents with geospatial SQL for real-time insights.
- Lakehouse ETL Guide: Stream object storage files into managed tables without silos.
Performance & Scale
- Performance Optimization: Enhance query performance with various strategies.
- Benchmarks: Compare Databend performance with other data warehouses.
- Data Lakehouse: Seamless integration with Hive, Iceberg, and Delta Lake.
Community & Support
- Join Slack: Chat with the Databend community and core engineers.
- Docs Issues: Report problems or request new coverage.
- Roadmap: Track upcoming features and share feedback.
- Email Us: Reach the team directly when you need help.
