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url: https://github.com/alibaba/AliSQL date_fetched: 2026-07-05 backfilled: true

Alibaba's Enterprise MySQL Branch with DuckDB OLAP & Native Vector Search

Battle-tested in Alibaba's production environment, powering millions of databases

Features • Quick Start • Docs • Roadmap • Contributing

AliSQL brings enterprise-grade capabilities to MySQL, combining the reliability of InnoDB OLTP with DuckDB's blazing-fast analytics and native vector search — all through familiar MySQL interfaces.

| DuckDB columnar engine delivers | Built-in HNSW algorithm supporting up to | Use your existing MySQL tools, drivers, and SQL — zero learning curve |

Feature	Description	Status
DuckDB Storage Engine	Columnar OLAP engine with automatic compression, perfect for analytics workloads	Available
Vector Index (VIDX)	Native vector storage & ANN search with HNSW, supports COSINE & EUCLIDEAN distance	Available
DDL Optimization	Instant DDL, parallel B+tree construction, non-blocking locks	Planned
RTO Optimization	Accelerated crash recovery for faster instance startup	Planned
Replication Boost	Binlog Parallel Flush, Binlog in Redo, large transaction optimization	Planned

# Clone the repository
git clone https://github.com/alibaba/AliSQL.git
cd AliSQL
# Build (release mode)
sh build.sh -t release -d ~/alisql
# Install
make install

Step-by-step guide:How to set up a DuckDB node

# Initialize data directory
~/alisql/bin/mysqld --initialize-insecure --datadir=~/alisql/data
# Start the server
~/alisql/bin/mysqld --datadir=~/alisql/data

-- Create an analytical table with DuckDB engine
CREATE TABLE sales_analytics (
    sale_date DATE,
    product_id INT,
    revenue DECIMAL(10,2),
    quantity INT
) ENGINE=DuckDB;
-- Run complex analytics (200x faster than InnoDB!)
SELECT
    DATE_FORMAT(sale_date, '%Y-%m') as month,
    SUM(revenue) as total_revenue,
    COUNT(*) as transactions
FROM sales_analytics
GROUP BY month
ORDER BY total_revenue DESC;

-- Create a table with vector column
CREATE TABLE embeddings (
    id INT PRIMARY KEY,
    content TEXT,
    embedding VECTOR(768)  -- 768-dimensional vectors
) ENGINE=InnoDB;
-- Create HNSW index for fast ANN search
CREATE VECTOR INDEX idx_embedding ON embeddings(embedding);
-- Find similar items using cosine distance
SELECT id, content,
       COSINE_DISTANCE(embedding, '[0.1, 0.2, ...]') as distance
FROM embeddings
ORDER BY distance
LIMIT 10;

Option	Description	Default
`-t release\|debug`	Build type	`debug`
`-d <dir>`	Installation directory	`/usr/local/alisql`
`-g asan\|tsan`	Enable sanitizer (memory/thread)	disabled
`-c`	Enable code coverage (gcov)	disabled

Prerequisites: CMake 3.x+, Python 3, GCC 7+ or Clang 5+

Q4 2025  ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
         [x] DuckDB Storage Engine  [x] Vector Index (VIDX)   [x] Open Source
2026     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
         [ ] DDL Optimization       [ ] RTO Optimization      [ ] Replication Boost
             - Instant DDL              - Fast Crash Recovery     - Binlog Parallel Flush
             - Parallel B+tree          - Minimize RTO            - Binlog in Redo
             - Non-blocking Locks                                 - Large TX Optimization

Document	Description
DuckDB Integration Guide	Complete guide for DuckDB storage engine
Vector Index Guide	Native vector storage and ANN search
Release Notes	What's new in AliSQL 8.0.44
Setup DuckDB Node	Quick setup guide for analytics

External Resources:

AliSQL became open source in December 2025 and is actively maintained by Alibaba Cloud Database Team.

We welcome contributions of all kinds!

Forkthe repository
Createa feature branch (- git checkout -b feature/amazing-feature)
Commityour changes (- git commit -m 'Add amazing feature')
Pushto the branch (- git push origin feature/amazing-feature)
Opena Pull Request

For bugs and feature requests, please use GitHub Issues.

RDSAI CLI is a next-generation, AI-powered CLI that transforms how you interact with AliSQL and MySQL databases. Describe your intent in natural language, and the AI agent handles the rest.

# Install
curl -LsSf https://raw.githubusercontent.com/aliyun/rdsai-cli/main/install.sh | sh
# Connect and ask in natural language
rdsai --host localhost -u root -p secret -D mydb
mysql> analyze index usage on users table
mysql> show me slow queries from the last hour
mysql> why this query is slow: SELECT * FROM users WHERE name LIKE '%john%'

Key Features:

Natural language to SQL conversion (English/中文)
AI-powered query optimization and diagnostics
Execution plan analysis with Ctrl+E
Multi-model LLM support (Qwen, OpenAI, DeepSeek, Anthropic, etc.)
Performance benchmarking with automated analysis

| For bug reports & feature requests | Managed DuckDB analytical instances |

AliSQL is licensed under GPL-2.0, the same license as MySQL.

See the LICENSE file for details.

Made with care by Alibaba Cloud Database Team