databend

App Listed

Data Agent Ready Warehouse : One for Analytics, Search, AI, Python Sandbox. — rebuilt from scratch. Unified architecture on your S3.

Checked · Sources

Downloads
48
Dependents
Not applicable
Stars
9,493
Forks
901
Contributors
226
Commits
34,932
Latest release

About

From the project README ·

Enterprise Data Warehouse for AI Agents
one warehouse for all your data

SQL analytics, vector search, and full-text search in a single Rust warehouse on object storage: fast, elastic, and grows with your data — with sandboxed Python UDFs for agents.

☁️ Try Cloud • 🚀 Quick Start • 📈 Performance • 📖 Documentation

databend

💡 Why Databend?

Databend is an open-source data warehouse built in Rust. Analytics, search, and agent workloads run on the same tables, so there is no second system to sync.

📊 One Warehouse
SQL analytics, vector search, full-text search, auto schema evolution, transactions.
🤖 Agent-Ready
Sandboxed Python UDFs for agent logic, SQL for orchestration.
🏢 Enterprise Scale
Fast vectorized engine, elastic compute on object storage: S3, Azure, GCS.
🌿 Branching
Git-like data versioning. Agents experiment safely on production snapshots.

Databend Architecture

📈 Performance

Published results on Databend Cloud with default settings. Each page includes the SQL to reproduce it.

Read the full README
BenchmarkResult
TPC-H SF100 vs. Snowflake1.25× faster, ~60% lower cost
Data ingestion vs. Snowflake5.15× faster, 91% lower cost
Vector & full-text search10M docs: vector p50 41 ms, full-text p50 35 ms
TPC-H SF1000 (1 TB) scaling4.1× faster on Large vs. Small warehouse

See all benchmarks.

⚡ Quick Start

Cloud (Recommended) — Sign up, create a warehouse, and run SQL in the worksheet. Cloud guide →

Self-hosted — Run the all-in-one image and connect with BendSQL:

docker run -d -p 127.0.0.1:8000:8000 datafuselabs/databend
bendsql -u root

See Docker image options and self-hosted deployment for credentials, storage, and production setup.

Your First Query

Analytics, full-text search, and vector search in one table:

CREATE TABLE docs (
    id INT,
    content STRING,
    embedding VECTOR(3),
    INVERTED INDEX content_idx(content),
    VECTOR INDEX embedding_idx(embedding) distance = 'cosine'
);

INSERT INTO docs VALUES
    (1, 'SQL analytics for agents', [1.0, 0.0, 0.0]),
    (2, 'Vector search for documents', [0.0, 1.0, 0.0]);

SELECT id, content FROM docs WHERE MATCH(content, 'analytics');

SELECT id, content FROM docs
ORDER BY COSINE_DISTANCE(embedding, [1.0, 0.0, 0.0]::VECTOR(3))
LIMIT 1;

Both queries return document 1. Learn more: Vector search · JSON & search.

🤖 Agent-Ready Architecture

Databend's Sandbox UDF enables flexible agent orchestration with a three-layer architecture:

  • Control Plane: Resource scheduling, permission validation, sandbox lifecycle management
  • Execution Plane (Databend): SQL orchestration, issues requests via Arrow Flight
  • Compute Plane (Sandbox Workers): Isolated sandboxes running your agent logic
-- Define your agent logic
CREATE FUNCTION my_agent(input STRING) RETURNS STRING
LANGUAGE python HANDLER = 'run'
AS $$
def run(input):
    # Your agent logic: LLM calls, tool use, reasoning...
    answer = f"processed: {input}"
    return answer
$$;

-- Orchestrate agents with SQL
SELECT my_agent(question) FROM tasks;

🚀 Use Cases

  • AI Agents: Sandbox UDF + SQL orchestration + branching for safe operations
  • Analytics & BI: Large-scale SQL analytics — Learn more
  • Search & RAG: Vector + full-text search — Learn more

🤝 Community & Support

Contributors are immortalized in the system.contributors table 🏆

📄 License

Databend is licensed under Apache 2.0. A small set of enterprise features is under Elastic 2.0, see LICENSING.md | Licensing FAQ


Enterprise warehouse, agent ready
🌐 Website • 🐦 Twitter

License
Apache-2.0
Crate facts
Not measured
  • Runs on, Native code and Python bindings read crates on crates.io. This entry lists no crate.

Compare with similar projects

Order: strongest tier first, then most downloads, then name, with unmeasured values last. A library counts downloads over 30 days. An app counts binary downloads per release. An app with none counts its crate downloads over 30 days. ML Rust runs this catalogue, so its closest project always gets a row.

databend beside the projects that share a topic with it
ProjectDownloadsDependentsStarsLatest releaseRuns on (GPU)Native codeLicense
databend This page App Listed

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48 binary downloads per release Not applicable 9,493 Not measured Not measured Apache-2.0
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vortex Listed

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compressr App New

Model conversion and quantization with no Python: reads SafeTensors, GGUF, TCF and PyTorch state dicts, writes SafeTensors, GGUF and TCF, and quantizes to Q2_K through Q8_0 and IQ4 formats, including Q4_K_M mixes. GPTQ, AWQ, NF4, FP8, EXL2 and ONNX input are not implemented.

Python bindings

23 downloads over 30 days Not applicable 0 0.2.1 GPU support unknown No native code found Apache-2.0
Why ListedNo archive, New or Featured rule places it, so it is Listed.

What it lacks for Featured

  • The check holds no value for Homebrew installs on request over 365 days, Docker pull growth over 90 days. A gate that lacks its signal does not pass.

What else the check found

  • The last activity is on 8 Nov 2026, 1 day ago. The rules expect an update within 365 days. Dormancy rule

Not measured: First release, Homebrew installs on request over 365 days, Docker pull growth over 90 days.

Exact rules: Listed, Featured app. The check on applied thresholds version 9.

Every rule outcome, as the check records it
  • expected-interval: app: E = 365 days
  • dormancy: last activity 2026-11-08, 1 days ago, E = 365: active
  • featured: not featured: unknown homebrew_on_request_365d, docker_pull_growth_90d
  • listed: listed: no archive, new or featured rule applies

Measurements and sources

Each signal row shows the raw value, its source and the fetch date. The Sources list gathers every distinct source on this page. Movement needs more history.

Sources5 sources
Adoption48 binary downloads per release4 not measured
Adoption measurements
SignalValueSourceFetchedCounts
Active dependentsNot measuredYes
New dependents (365 days)Not measuredYes
Peak active dependentsNot measuredYes
Active dependents as a share of the peakNot measuredYes
Binary downloads per release48GitHub releasesYes
MaintenanceLatest human commit: 1 day ago7 not measured
Maintenance measurements
SignalValueSourceFetchedCounts
Latest human commit2026-11-08GitHub repositoryYes
Latest release2026-11-08GitHub releasesYes
First releaseNot measuredYes
Latest versionNot measuredYes
Days the oldest outside issue waits for a reply0GitHub repositoryYes
Maintainer replies over 365 days128GitHub repositoryYes
Repository archivedfalseGitHub repositoryYes
Repository gonefalseGitHub repositoryYes
Release commit or manifest in the repoNot measuredYes
Published docsNot measuredYes
Latest release fails cargo checkNot measuredYes
Build check dateNot measuredYes
Build check toolchainNot measuredYes
SecurityNot measured
Security measurements
SignalValueSourceFetchedCounts
Unpatched vulnerabilities past the grace windowNot measuredYes
RustSec unmaintained advisoryNot measuredYes
Deprecation noticeNot measuredYes
Deprecated requirementNot measuredYes
Distribution144 binary downloads over the last 3 releases9 not measured
Distribution measurements
SignalValueSourceFetchedCounts
ReleasesNot measuredYes
Downloads over 30 daysNot measuredYes
Binary downloads over the last 3 releases144GitHub releasesYes
Homebrew installs on request over 365 daysNot measuredYes
Repology repository families1Repology projectYes
Docker pull growth over 90 daysNot measuredYes
Docker pulls at the growth baselineNot measuredYes
Every version a prereleaseNot measuredYes
Every version 0.0.xNot measuredYes
Every version yankedNot measuredYes
Crate deleted from crates.ioNot measuredYes
Repository9,493 stars, 901 forks, 226 contributors, 34,932 commits. Stars alone never qualify a project.1 not measured
Repository measurements
SignalValueSourceFetchedCounts
GitHub stars9493GitHub repositoryYes — one part of the repository route
GitHub forks901GitHub repositoryYes — one part of the repository route
Contributors with a GitHub account226GitHub contributorsYes — one part of the repository route
Commits on the default branch34932GitHub repositoryNo
Repository's main crate left out of the entryNot measuredYes
Facts that never count
Facts that never count measurements
SignalValueSourceFetchedCounts
LicenseApache-2.0GitHub repositoryNo
Runs on, from listed crates and their direct dependenciesNot measuredNo
What shows each backendNot measuredNo
Native code, from listed crates and their dependenciesNot measuredNo
Python bindings, from direct dependencies of listed cratesNot measuredNo
Crates that depend on a listed crate directlyNot measuredNo

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