AI’s Impact on Open‑Source Databases: MySQL, PostgreSQL, and AliSQL DuckDB

Database Landscape in 2026

The open‑source database ecosystem remains dynamic. MySQL, historically driven by Oracle, faces community concerns about its future, while PostgreSQL has risen to fourth place on DB‑Engines rankings and is the fastest‑growing open‑source relational database.

AI as a New Driver for Databases

In the era of Agentic AI, databases are evolving from simple storage layers to security, governance, and execution platforms for AI agents. Autonomous‑operation projects such as OpenClaw and RDSClaw illustrate this shift.

MySQL vs PostgreSQL: Market and Technical Gaps

PostgreSQL is becoming the preferred choice for new AI‑related projects. MySQL 8.0 will lose community support in April 2026, and its development of AI‑centric features (OLAP, vector search) lags behind PostgreSQL.

AliSQL Open‑Source Releases (Feb 2026)

AliSQL announced three major open‑source components:

AliSQL DuckDB : a columnar storage engine integrated into MySQL.

AliSQL Vector Engine : a vectorized execution layer derived from MariaDB, benchmarked against pgvector.

AliSQL‑CLI : an intelligent command‑line tool with built‑in large‑model connectivity.

AliSQL DuckDB Integration

The DuckDB columnar engine can accelerate analytical queries up to 200× without modifying existing applications. It enables in‑database analytics, eliminating costly ETL pipelines and allowing real‑time AI model training directly on the data.

Vectorized Engine

The vector engine supports both scalar and vector queries in a single MySQL instance. It provides vector data types and similarity search functions comparable to pgvector, allowing users to keep data in MySQL while handling AI‑driven workloads.

Intelligent CLI

AliSQL‑CLI embeds LLM connectivity, offering natural‑language query translation, automated diagnostics, and SQL generation. Users can ask questions such as “Why is this query slow?” and receive actionable recommendations.

Performance and Hardware Acceleration

AliSQL collaborates with AMD to optimize HTAP workloads on EPYC processors (Zen 5 architecture). Benchmarks show a 50% improvement in TPC‑H sf100 query performance on the latest AMD generation, with IPC up +17 %, AI‑specific compute up +37 %, and memory bandwidth up +33 % (AVX‑512, 3 nm/4 nm process).

Future Directions

Support for Iceberg table format on S3, enabling “write‑once, analyze‑many” data lake workflows.

Deep integration with Spark, Flink, and DuckDB for unified HTAP pipelines.

Gradual open‑sourcing of enterprise‑grade features such as high‑throughput transaction optimizations and flash‑sale scenario tuning.

Community Evolution

AliSQL originated as an internal MySQL branch (2010‑2015), became fully open‑source (2016‑2020), and since 2021 has focused on AI‑centric enhancements. The project aims to contribute back to the global MySQL ecosystem while positioning itself as a first‑choice data foundation for AI applications.