aurora-data-api
A Python DB-API 2.0 client for the AWS Aurora Serverless Data API
Decision gist · record as of 2026-08-14
Yes, if you are building serverless applications on AWS Lambda that need Aurora database access. The package solves a real architectural problem (stateless HTTP vs. broken connection pools) and has low install friction. However, the last release was December 2023 and there have been no updates since; verify that it still works with your Aurora version and Python release before committing to production.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires an AWS Aurora Serverless cluster with Data API enabled, credentials stored in AWS Secrets Manager, and AWS credentials configured locally or via IAM role.
- Low friction: pure Python wheel with a single runtime dependency on boto3.
- Maintenance has aged since the last release in December 2023, but the repository remains active with a recent commit in August 2025 and no archived status.
License · maintenance · safety
Apache Software License (permissive) — Licensed under Apache License 2.0 (permissive), allowing commercial use, modification, and distribution with minimal restrictions—suitable for most production and proprietary projects.
last release 2023-12-29 (959 days) · last repo commit 2025-08-20 · 104 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 106,115 downloads/mo, #12,668 on PyPI
Alternatives
Verify before relying
pip install aurora-data-api
import aurora_data_api
with aurora_data_api.connect(
aurora_cluster_arn="arn:aws:rds:...:cluster:my-cluster",
secret_arn="arn:aws:secretsmanager:...:secret:...",
database="my_db"
) as conn:
with conn.cursor() as cursor:
cursor.execute("select * from pg_catalog.pg_tables")
print(cursor.fetchall())- Whether cursor iteration with server-side pagination works reliably for very large result sets in production Lambda environments.
- Performance characteristics compared to traditional connection pooling for high-frequency query workloads.
What it is and what it does
aurora-data-api is a Python DB-API 2.0 driver that connects to AWS Aurora Serverless databases through the RDS Data API, which tunnels SQL over HTTP rather than using traditional TCP connections. It implements the standard DB-API interface (connect, cursor, execute, fetch) so it works like any other database driver in Python code.
The package solves a specific problem for AWS Lambda and other serverless environments: traditional database drivers maintain stateful connection pools that break across Lambda freeze-thaw cycles, while the Data API uses stateless HTTP and AWS IAM authentication. It requires boto3 as its only runtime dependency and works with Aurora PostgreSQL and MySQL clusters that have the Data API endpoint enabled.
Use it for
- Query Aurora databases from AWS Lambda functions without managing connection pools or handling credential rotation.
- Build serverless applications that need database access without opening database ports to the Lambda IP pool.
- Use standard DB-API 2.0 code patterns (cursor iteration, parameterized queries) against Aurora via HTTP.
- Integrate with SQLAlchemy using the companion sqlalchemy-aurora-data-api dialect for ORM-based serverless apps.
- Migrate existing DB-API code to serverless by swapping the driver while keeping query logic unchanged.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building serverless applications on AWS Lambda that need Aurora database access.
The package solves a real architectural problem (stateless HTTP vs. broken connection pools) and has low install friction. However, the last release was December 2023 and there have been no updates since; verify that it still works with your Aurora version and Python release before committing to production.
Install
aurora-data-api on PyPI
Before you install
Low friction: pure Python wheel with a single runtime dependency on boto3. Maintenance has aged since the last release in December 2023, but the repository remains active with a recent commit in August 2025 and no archived status.
Requires an AWS Aurora Serverless cluster with Data API enabled, credentials stored in AWS Secrets Manager, and AWS credentials configured locally or via IAM role.
License in practice
Licensed under Apache License 2.0 (permissive), allowing commercial use, modification, and distribution with minimal restrictions—suitable for most production and proprietary projects.
Quickstart
pip install aurora-data-api
import aurora_data_api
with aurora_data_api.connect(
aurora_cluster_arn="arn:aws:rds:...:cluster:my-cluster",
secret_arn="arn:aws:secretsmanager:...:secret:...",
database="my_db"
) as conn:
with conn.cursor() as cursor:
cursor.execute("select * from pg_catalog.pg_tables")
print(cursor.fetchall())Verify before relying
- Whether cursor iteration with server-side pagination works reliably for very large result sets in production Lambda environments.
- Performance characteristics compared to traditional connection pooling for high-frequency query workloads.
Package facts
| License | Apache Software License permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packageboto3 |
| Maintenance | Aging 959 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 106,115 / month, #12,668 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Intended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseOperating System :: MacOS :: MacOS XOperating System :: POSIXProgramming Language :: PythonProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Software Development :: Libraries :: Python Modules |
Evidence: aurora_data_api-0.5.0-py3-none-any.whl
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See also aws-advanced-python-wrapper · sqlalchemy-aurora-data-api · sqlalchemy-rdsiam · redshift-connector · hdbcli · cdk-aurora-globaldatabase · pymssql · PyAthena · pydynamodb · singlestoredb