sqlalchemy-cubrid

SQLAlchemy 2.0–2.1 dialect for the CUBRID database — Python ORM, schema reflection, Alembic migrations, and type mapping for SQLAlchemy and CUBRID-specific types.

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Status: Production/Stable — sqlalchemy-cubrid is a maintained SQLAlchemy dialect for CUBRID supporting SQLAlchemy 2.0–2.1 and CUBRID 10.2–11.4. Note: Versions prior to 1.0.0 used inconsistent numbering (0.x, 2.x). The canonical version history starts at 1.0.0.

Why sqlalchemy-cubrid?

CUBRID is a high-performance open-source relational database, widely adopted in Korean public-sector and enterprise applications. Until now, there was no actively maintained SQLAlchemy dialect that supports the modern 2.0–2.1 API.

sqlalchemy-cubrid bridges that gap:

• Full SQLAlchemy 2.0–2.1 dialect with statement caching and PEP 561 typing
• Extensive offline test suite — no database required to run it; CI enforces a minimum 95% line-coverage gate (--cov-fail-under=95 in the offline-tests job, CI badge above)
• Concurrency stress tests — QueuePool sync threaded + asyncio.gather workloads validated against live CUBRID
• SQLAlchemy 2.1-ready compat shim — private API access wrapped in _compat.py; dependency pin now >=2.0,<2.3 covering SA 2.0 and 2.1
• Tested against 4 CUBRID versions (10.2, 11.0, 11.2, 11.4) across Python 3.11 -- 3.14
• CUBRID-specific DML constructs: ON DUPLICATE KEY UPDATE, MERGE, REPLACE INTO
• Alembic migration support out of the box
• Three driver options — pure Python (cubrid+pycubrid://, recommended), async pure Python (cubrid+aiopycubrid://), or the legacy C-extension (cubrid:// / cubrid+cubriddb://)

Support Status

• Status: Production/Stable
• Supported matrix: SQLAlchemy >=2.0,<2.3, CUBRID 10.2, 11.0, 11.2, 11.4, Python 3.11–3.14
• Ordinary PRs run the full offline suite with the 95% coverage floor on one Ubuntu/Python 3.12 lane; high-risk changes add newest live integration. Main/changed-weekly runs use oldest/newest endpoints. The full supported integration matrix remains manual and release-gated. See CI execution policy.
• SQLAlchemy 2.1 pre-releases are exercised by a non-gating --pre canary CI job
• See Known Limitations for behavior boundaries and unsupported features

Architecture

flowchart TD
    app["Application"] --> sa["SQLAlchemy Core/ORM"]
    sa --> dialect["CubridDialect"]
    dialect --> pycubrid["pycubrid driver"]
    dialect --> cext["CUBRIDdb driver"]
    dialect --> aio["pycubrid.aio async driver"]
    pycubrid --> server["CUBRID Server"]
    cext --> server
    aio --> server

flowchart TD
    expr["SQL Expression"] --> compiler["CubridSQLCompiler"] --> sql["SQL String"]

Requirements

Python 3.10 support retirement: Python 3.10 reached upstream end of life on 2026-10-01 (PEP 619). The 1.8.x and 1.9.x lines support Python 3.10; 1.9.0 carried the advance notice. From 1.10.0 the package requires Python 3.11 or newer, so pip on Python 3.10 keeps installing 1.9.x. Upgrade your interpreter, recreate your virtual environment and validate your application before upgrading.

• Python 3.11 or later
• SQLAlchemy 2.0 – 2.1
• pycubrid (pure Python, recommended) or the legacy CUBRIDdb C extension built from cubrid-python v11.3.0.51 or later

Installation

pip install sqlalchemy-cubrid

With the pure Python driver (sync and async):

pip install "sqlalchemy-cubrid[pycubrid]"

The [pycubrid] extra supports both cubrid+pycubrid:// and cubrid+aiopycubrid://. It includes SQLAlchemy's asyncio extra (greenlet); greenlet may need build tools if a compatible wheel is unavailable.

With Alembic support:

pip install "sqlalchemy-cubrid[alembic]"

With the legacy CUBRIDdb C-extension driver (the bare cubrid:// URL), build CUBRIDdb from cubrid-python v11.3.0.51 or later; see Driver Compatibility.

The [cubrid] and [cubriddb] extras are deprecated. They install the CUBRID-Python package from PyPI, whose newest release is 9.3.x (2015). That release is untested with this dialect: it returns BIGINT as str and fails parts of the integration suite. The dialect warns (SAWarning) at the first connection when it finds a CUBRIDdb older than 11.3. For new projects, use the recommended pure-Python [pycubrid] driver (the cubrid+pycubrid:// URL). To select the legacy C-extension driver explicitly, use the cubrid+cubriddb:// URL.

Quick Start

Core (Connection-Level)

from sqlalchemy import create_engine, text

engine = create_engine("cubrid+pycubrid://dba:password@localhost:33000/demodb")

with engine.connect() as conn:
    result = conn.execute(text("SELECT 1"))
    print(result.scalar())

ORM (Session-Level)

from sqlalchemy import create_engine, String
from sqlalchemy.orm import DeclarativeBase, Mapped, Session, mapped_column


class Base(DeclarativeBase):
    pass


class User(Base):
    __tablename__ = "users"

    id: Mapped[int] = mapped_column(primary_key=True, autoincrement=True)
    name: Mapped[str] = mapped_column(String(100))
    email: Mapped[str] = mapped_column(String(200), unique=True)


engine = create_engine("cubrid+pycubrid://dba:password@localhost:33000/demodb")
Base.metadata.create_all(engine)

with Session(engine) as session:
    user = User(name="Alice", email="alice@example.com")
    session.add(user)
    session.commit()

Async

from sqlalchemy.ext.asyncio import create_async_engine, AsyncSession
from sqlalchemy import text

engine = create_async_engine("cubrid+aiopycubrid://dba:password@localhost:33000/demodb")

async with AsyncSession(engine) as session:
    result = await session.execute(text("SELECT 1"))
    print(result.scalar())

Async insert with PK retrieval

CUBRID has no RETURNING clause. For ORM inserts, call await session.flush() inside the transaction block to populate the auto-increment PK on the object before commit:

from sqlalchemy.ext.asyncio import create_async_engine, AsyncSession
from sqlalchemy import String
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column

class Base(DeclarativeBase):
    pass

class User(Base):
    __tablename__ = "users"
    id: Mapped[int] = mapped_column(primary_key=True, autoincrement=True)
    name: Mapped[str] = mapped_column(String(100))

engine = create_async_engine("cubrid+aiopycubrid://dba:password@localhost:33000/demodb")

async with AsyncSession(engine) as session:
    async with session.begin():
        user = User(name="Alice")
        session.add(user)
        await session.flush()  # populates user.id without committing
        print(f"Inserted id={user.id}")

For raw Core inserts where you need the auto-increment PK, run SELECT LAST_INSERT_ID() after the statement (see Known Limitations).

Features

• Type mapping for SQLAlchemy standard and CUBRID-specific types — numeric, string, date/time, bit, LOB, collection, and JSON types
• SQL compilation -- SELECT, JOIN, CAST, LIMIT/OFFSET, subqueries, CTEs, window functions
• DML extensions -- ON DUPLICATE KEY UPDATE, MERGE, REPLACE INTO, FOR UPDATE, TRUNCATE
• DDL support -- COMMENT, IF NOT EXISTS / IF EXISTS, AUTO_INCREMENT
• Schema reflection -- tables, views, columns, PKs, FKs, indexes, unique constraints, comments
• Alembic migrations via CubridImpl (registered automatically when the dialect loads)
• Three CUBRID MVCC isolation levels — READ COMMITTED (default), REPEATABLE READ, SERIALIZABLE
• Async support — create_async_engine("cubrid+aiopycubrid://...") via pycubrid.aio

Known Limitations

• No RETURNING — INSERT/UPDATE/DELETE ... RETURNING not supported; for ORM use await session.flush() to populate id on the object (see Async Quick Start), or for Core use cursor.lastrowid / SELECT LAST_INSERT_ID() after the statement
• No sequences — CUBRID uses AUTO_INCREMENT only
• Single effective schema — CUBRID exposes one schema per connection (the current user's schema); get_schema_names() reports that one schema and every reflection method honours schema= consistently (the default schema is reflected; any other schema yields no tables/views). Owner-qualified cross-schema reflection is not supported.
• Uncommitted DDL holds schema locks — CUBRID DDL is transactional (ROLLBACK undoes it; only client autocommit, which the dialect turns off, commits it early), so by default a whole Alembic upgrade is one transaction (transactional_ddl = True) and keeps the tables it touches locked until it commits; use transaction_per_migration=True for long or large-table migrations
• SQLAlchemy 2.0–2.1 only — pinned to <2.3; SA 2.1 pre-releases are forward-tested via shims and a --pre canary CI job (details)
• Async requires pycubrid >= 1.8.0,<2.0 — the cubrid+aiopycubrid:// driver needs the async-capable pycubrid package line currently supported by this project
• CARDINALITY() broken — func.cardinality() raises CompileError with workaround guidance; the CUBRID server has a known bug
• Reserved words auto-quoted — Column names matching CUBRID reserved words (day, count, value, etc.) are automatically double-quoted in DDL; see reserved word list
• Timezone type reflection — CUBRID's TIMESTAMPTZ, TIMESTAMPLTZ, DATETIMETZ and DATETIMELTZ reflect as distinct SQLAlchemy types (sqlalchemy_cubrid.TIMESTAMPTZ/TIMESTAMPLTZ/DATETIMETZ/DATETIMELTZ, each with timezone=True) rather than collapsing into plain TIMESTAMP/DATETIME (#181, #442); see Type Mapping

Documentation

Compatibility Matrix

FAQ

How do I connect to CUBRID with SQLAlchemy?

from sqlalchemy import create_engine
engine = create_engine("cubrid+pycubrid://dba:password@localhost:33000/demodb")

The recommended way is the pure-Python pycubrid driver: create_engine("cubrid+pycubrid://dba:password@localhost:33000/demodb"). The driver requires no CUBRID native libraries. The [pycubrid] extra also installs greenlet for SQLAlchemy's async bridge; it may require build tools when no compatible wheel is available. The bare cubrid:// URL uses the legacy CUBRIDdb C-extension driver, which must be built from cubrid-python v11.3.0.51 or later (the PyPI CUBRID-Python 9.3.x release that the deprecated [cubriddb] extra installs is untested); to select it explicitly and unambiguously use cubrid+cubriddb://.

Does sqlalchemy-cubrid support SQLAlchemy 2.0–2.1?

Yes. sqlalchemy-cubrid is built for SQLAlchemy 2.0–2.1 and supports the 2.0-style API including Session.execute(), typed Mapped[] columns, and statement caching.

Does sqlalchemy-cubrid support Alembic migrations?

Yes. Install with pip install "sqlalchemy-cubrid[alembic]". The CUBRID migration implementation registers itself when the dialect loads, so the default env.py works unchanged with synchronous URLs; for cubrid+aiopycubrid://, use Alembic's async template (alembic init -t async). CUBRID DDL is transactional, so by default a failed alembic upgrade is rolled back whole, version bump included; set transaction_per_migration=True to commit after each revision for long or large-table migrations.

What Python versions are supported?

Python 3.11, 3.12, 3.13, and 3.14.

Does CUBRID support RETURNING clauses?

No. CUBRID does not support INSERT ... RETURNING or UPDATE ... RETURNING. Use cursor.lastrowid or SELECT LAST_INSERT_ID() instead.

How do I use ON DUPLICATE KEY UPDATE with CUBRID?

from sqlalchemy_cubrid import insert
stmt = insert(users).values(name="Alice").on_duplicate_key_update(name="Alice Updated")

What's the difference between cubrid:// and cubrid+pycubrid://?

cubrid:// uses the C-extension driver (CUBRIDdb) which requires compilation. cubrid+pycubrid:// uses the pure Python driver, which requires no CUBRID native libraries. The [pycubrid] extra includes greenlet, whose installation may require build tools when no compatible wheel is available. cubrid+aiopycubrid:// uses the async variant of the pure Python driver for use with create_async_engine and AsyncSession.

Recommendation: for new projects prefer cubrid+pycubrid:// (pure Python driver, no CUBRID native libraries). The [pycubrid] extra's greenlet dependency may need build tools. Use cubrid+cubriddb:// with CUBRIDdb built from cubrid-python v11.3.0.51 or later when you specifically need the legacy C-extension driver.

Does sqlalchemy-cubrid support async?

Yes. Use create_async_engine("cubrid+aiopycubrid://...") with the pycubrid async driver. Requires pycubrid>=1.8.0,<2.0. Both pycubrid dialects use native Connection.ping(False) / AsyncConnection.ping(False) for pool_pre_ping, and all Core and ORM features work with AsyncSession.

Related Projects

• pycubrid — Pure Python DB-API 2.0 driver for CUBRID
• cubrid-cookbook-python — Production-ready Python examples for CUBRID

Roadmap

See ROADMAP.md for this project's direction and next milestones.

For the ecosystem-wide view, see the CUBRID Labs Ecosystem Roadmap.

Contributing

See CONTRIBUTING.md for guidelines and docs/DEVELOPMENT.md for development setup.

First contribution

New to CUBRID? Pick the repository that matches what you want to work on:

• Documentation and runnable examples: cubrid-cookbook-python
• Pure-Python driver fixes: pycubrid
• SQLAlchemy dialect fixes: sqlalchemy-cubrid

Most first issues can be developed and tested with the offline checks in CONTRIBUTING.md — no Docker or CUBRID server needed. Live CUBRID verification can be completed by CI and maintainers.

Browse open good first issue tasks.

Security

Report vulnerabilities via email -- see SECURITY.md. Do not open public issues for security concerns.

Disclaimer

This project is part of CUBRID Lab, an independent open-source initiative for CUBRID developer tooling, and is not affiliated with, sponsored by, or endorsed by CUBRID Corporation or the official CUBRID project.

License

MIT -- see LICENSE.