tiledb
Pythonic interface to the TileDB array storage manager
Decision gist · record as of 2026-08-14
Yes, if you work with multi-dimensional array data and need efficient storage and querying. The active maintenance, permissive MIT license, and broad platform support make it a solid choice. Medium install friction is acceptable for the performance gains it offers. No known vulnerabilities as of the fact sheet date.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires numpy and packaging at runtime; optional Pandas and PyArrow for dataframe functionality.
- Medium install friction: prebuilt wheels cover Python 3.10–3.13 on macOS (both ARM and x86), Linux (glibc 2.28+), and Windows, but the underlying TileDB C++ library must be present or bundled.
- Active maintenance with a recent release 170 days ago.
License · maintenance · safety
MIT (permissive) — MIT license is permissive; you may use, modify, and distribute tiledb freely in commercial and private projects with minimal restrictions.
last release 2026-02-25 (170 days) · last repo commit 2026-07-16 · 202 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 89,107 downloads/mo, #13,680 on PyPI
Alternatives
Verify before relying
pip install tiledb
import tiledb
import numpy as np
# Create and write to an array
with tiledb.open('my_array.tdb', mode='w') as A:
A[:] = np.arange(10)- Whether the prebuilt wheels include the full TileDB C++ runtime or require a separate system installation.
- Performance characteristics and scalability limits for typical array sizes and query patterns.
- Cloud storage backend support and any authentication requirements.
What it is and what it does
TileDB-Py is a Python binding to the TileDB array storage engine, a columnar array database designed for efficient storage and retrieval of multi-dimensional data. It abstracts away the complexity of managing dense and sparse arrays, offering a NumPy-like interface for reading, writing, and querying array data. The package depends on numpy for numerical operations and packaging for version handling.
Typical workflows involve creating arrays with defined schemas, populating them with data via numpy arrays or Pandas DataFrames, and then querying slices or ranges efficiently. It targets scientific computing, geospatial analysis, and time-series workloads where traditional row-oriented databases are inefficient. The library is actively maintained, supports Python 3.9 through 3.13, and offers prebuilt wheels for major platforms.
Use it for
- Store and query large geospatial raster datasets with efficient spatial indexing.
- Manage time-series data from sensors or financial markets with fast range queries.
- Build scientific computing pipelines that work with multi-dimensional arrays.
- Replace row-oriented storage when you need better compression and query performance.
- Integrate array data into machine learning workflows via Pandas DataFrames.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you work with multi-dimensional array data and need efficient storage and querying.
The active maintenance, permissive MIT license, and broad platform support make it a solid choice. Medium install friction is acceptable for the performance gains it offers. No known vulnerabilities as of the fact sheet date.
Install
tiledb on PyPI
Before you install
Medium install friction: prebuilt wheels cover Python 3.10–3.13 on macOS (both ARM and x86), Linux (glibc 2.28+), and Windows, but the underlying TileDB C++ library must be present or bundled. Active maintenance with a recent release 170 days ago.
Requires numpy and packaging at runtime; optional Pandas and PyArrow for dataframe functionality.
License in practice
MIT license is permissive; you may use, modify, and distribute tiledb freely in commercial and private projects with minimal restrictions.
Quickstart
pip install tiledb
import tiledb
import numpy as np
# Create and write to an array
with tiledb.open('my_array.tdb', mode='w') as A:
A[:] = np.arange(10)Verify before relying
- Whether the prebuilt wheels include the full TileDB C++ runtime or require a separate system installation.
- Performance characteristics and scalability limits for typical array sizes and query patterns.
- Cloud storage backend support and any authentication requirements.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 2 packagesnumpypackaging |
| Maintenance | Actively maintained 170 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 89,107 / month, #13,680 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersIntended Audience :: Information TechnologyIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseOperating System :: MacOS :: MacOS XOperating System :: POSIX :: LinuxOperating System :: UnixProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.9Topic :: Software Development :: Libraries :: Python Modules |
Evidence: tiledb-0.36.1-cp310-cp310-macosx_11_0_arm64.whl; tiledb-0.36.1-cp310-cp310-macosx_11_0_x86_64.whl; tiledb-0.36.1-cp310-cp310-manylinux_2_28_aarch64.whl; tiledb-0.36.1-cp310-cp310-manylinux_2_28_x86_64.whl; tiledb-0.36.1-cp310-cp310-win_amd64.whl; tiledb-0.36.1-cp311-cp311-macosx_11_0_arm64.whl; tiledb-0.36.1-cp311-cp311-macosx_11_0_x86_64.whl; tiledb-0.36.1-cp311-cp311-manylinux_2_28_aarch64.whl; tiledb-0.36.1-cp311-cp311-manylinux_2_28_x86_64.whl; tiledb-0.36.1-cp311-cp311-win_amd64.whl; tiledb-0.36.1-cp312-cp312-macosx_11_0_arm64.whl; tiledb-0.36.1-cp312-cp312-macosx_11_0_x86_64.whl; tiledb-0.36.1-cp312-cp312-manylinux_2_28_aarch64.whl; tiledb-0.36.1-cp312-cp312-manylinux_2_28_x86_64.whl; tiledb-0.36.1-cp312-cp312-win_amd64.whl; tiledb-0.36.1-cp313-cp313-macosx_11_0_arm64.whl; tiledb-0.36.1-cp313-cp313-macosx_11_0_x86_64.whl; tiledb-0.36.1-cp313-cp313-manylinux_2_28_aarch64.whl; tiledb-0.36.1-cp313-cp313-manylinux_2_28_x86_64.whl; tiledb-0.36.1-cp313-cp313-win_amd64.whl
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