deltalake
Native Delta Lake Python binding based on delta-rs with Pandas integration
Decision gist · record as of 2026-08-14
Yes, if you work with Delta Lake tables in Python. The package is actively maintained, has no known vulnerabilities, supports current Python versions, and integrates well with Pandas. Medium install friction is acceptable for the functionality gained. Not necessary if you don't use Delta Lake or prefer alternative data formats.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Official wheels are statically linked against OpenSSL for remote object store communication.
- Medium install friction due to compiled wheels; the package provides prebuilt binaries for common platforms (x86_64, ARM64, macOS, Linux, Windows) but requires Python 3.10 or later.
License · maintenance · safety
permissive license (permissive) — Licensed under Apache Software License (permissive), allowing commercial use, modification, and distribution with minimal restrictions.
last release 2026-07-08 (37 days) · last repo commit 2026-08-10 · 3,282 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 29,502,842 downloads/mo, #813 on PyPI
Alternatives
Verify before relying
pip install deltalake
from deltalake import DeltaTable
dt = DeltaTable("path/to/delta/table")
version = dt.version()
df = dt.to_pandas()- Performance characteristics and scalability limits for large Delta tables or high-throughput workloads.
- Compatibility with specific cloud storage backends (S3, Azure, GCS) beyond the example shown.
- Whether OpenTelemetry tracing is production-ready or still experimental.
What it is and what it does
Deltalake is a Python library that wraps delta-rs, the Rust implementation of Delta Lake, to give Python developers native access to Delta tables. It lets you read, write, and manage Delta Lake data formats directly from Python, with built-in Pandas integration for easy conversion to and from DataFrames. The library also supports OpenTelemetry tracing for observability and debugging of Delta operations.
The package is built on compiled Rust code exposed through Python bindings, which means installation requires prebuilt wheels for your platform. It depends on arro3-core for Arrow data handling and the deprecated library for compatibility. It's designed for data engineers and analysts working with Delta Lake in data pipelines, analytics workflows, or data lake architectures where Python is the primary language.
Use it for
- Read Delta tables from cloud storage (S3, etc.) and convert them to Pandas DataFrames for analysis.
- Write Pandas DataFrames to Delta Lake format with ACID transaction guarantees.
- Query Delta table metadata (version history, file URIs, schema) for data governance and auditing.
- Build data pipelines that combine Delta Lake operations with Python data processing workflows.
- Enable OpenTelemetry tracing on Delta operations for performance monitoring and debugging.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you work with Delta Lake tables in Python.
The package is actively maintained, has no known vulnerabilities, supports current Python versions, and integrates well with Pandas. Medium install friction is acceptable for the functionality gained. Not necessary if you don't use Delta Lake or prefer alternative data formats.
Install
deltalake on PyPI
Before you install
Medium install friction due to compiled wheels; the package provides prebuilt binaries for common platforms (x86_64, ARM64, macOS, Linux, Windows) but requires Python 3.10 or later. Actively maintained with recent releases and no known vulnerabilities.
Requires Python 3.10 or later. Official wheels are statically linked against OpenSSL for remote object store communication.
License in practice
Licensed under Apache Software License (permissive), allowing commercial use, modification, and distribution with minimal restrictions.
Quickstart
pip install deltalake
from deltalake import DeltaTable
dt = DeltaTable("path/to/delta/table")
version = dt.version()
df = dt.to_pandas()Verify before relying
- Performance characteristics and scalability limits for large Delta tables or high-throughput workloads.
- Compatibility with specific cloud storage backends (S3, Azure, GCS) beyond the example shown.
- Whether OpenTelemetry tracing is production-ready or still experimental.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 2 packagesarro3-coredeprecated |
| Maintenance | Actively maintained 37 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 29,502,842 / month, #813 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: Apache Software LicenseProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14 |
Evidence: deltalake-1.6.2-cp310-abi3-macosx_10_12_x86_64.whl; deltalake-1.6.2-cp310-abi3-macosx_11_0_arm64.whl; deltalake-1.6.2-cp310-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; deltalake-1.6.2-cp310-abi3-manylinux_2_28_aarch64.whl; deltalake-1.6.2-cp310-abi3-musllinux_1_2_aarch64.whl; deltalake-1.6.2-cp310-abi3-musllinux_1_2_x86_64.whl; deltalake-1.6.2-cp310-abi3-win_amd64.whl
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See also delta-kernel-rust-sharing-wrapper · hops-deltalake · deltalite · delta-sharing · delta-spark · mltable · pyarrowfs-adlgen2 · autosar-data · awswrangler · dbt-databricks