TileDB-Inc/TileDB
TileDB-Inc/TileDB has 2,093 GitHub stars and 214 forks. GitHot measured 0 stars in 24 hours and +2 in 7 days. Last checked 2026-11-13 15:59 UTC. Last push 2026-10-20.
計測したスター増加
- 24時間
- 0
- 7日間
- +2
- 15日間
- 履歴を収集中
- 1か月
- 履歴を収集中
期間ごとの純増数です。期間は重複しており、日別の値ではありません。未計測の値は空欄です。スター数は注目度の指標であり、品質の保証ではありません。
概要
The Universal Storage Engine
データREADME.md
オリジナルThe Universal Storage Engine
TileDB is a powerful engine for storing and accessing dense and sparse multi-dimensional arrays, which can help you model any complex data efficiently. It is an embeddable C++ library that works on Linux, macOS, and Windows. It is open-sourced under the permissive MIT License, developed and maintained by TileDB, Inc. To distinguish this project from other TileDB offerings, we often refer to it as TileDB Embedded.
TileDB includes the following features:
- Support for both dense and sparse arrays
- Support for dataframes and key-value stores (via sparse arrays)
- Cloud storage (AWS S3, Google Cloud Storage, Azure Blob Storage)
- Chunked (tiled) arrays
- Multiple compression, encryption and checksum filters
- Fully multi-threaded implementation
- Parallel IO
- Data versioning (rapid updates, time traveling)
- Array metadata
- Array groups
- Numerous APIs on top of the C++ library
- Numerous integrations (Spark, Dask, MariaDB, GDAL, etc.)
You can use TileDB to store data in a variety of applications, such as Genomics, Geospatial, Finance and more. The power of TileDB stems from the fact that any data can be modeled efficiently as either a dense or a sparse multi-dimensional array, which is the format used internally by most data science tooling. By storing your data and metadata in TileDB arrays, you abstract all the data storage and management pains, while efficiently accessing the data with your favorite data science tool.
Quickstart
You can install the TileDB C++ library as follows:
# Conda (macOS, Linux, Windows):
$ conda install -c conda-forge tiledb
Visit the links below for Python, R, and other APIs installation instructions.
Alternatively, you can use the Dockerfile we provide.
We include several examples. You can start with the following:
Documentation
You can find the detailed TileDB documentation at https://cloud.tiledb.com/academy.
Building from source
To build TileDB from source, visit Building from Source.
Format Specification
The TileDB data format is open-source and can be found here.
Application-specific Packages
- TileDB-BioImaging: TileDB library for biomedical imaging, with support for image-optimized compression using WebP.
- TileDB-SOMA: TileDB implementation of the SOMA specification for single-cell genomic data. (documentation)
- TileDB-VCF: TileDB library and query engine for genomic variant data. (documentation).
- TileDB-Vector-Search: open source, embeddable, and cloud-native vector similarity search database built on top of TileDB in high-performance C++, with an easy-to-use Python API.
APIs
The TileDB team maintains a variety of APIs built on top of the C++ library:
Get involved
TileDB Embedded is an open-source project and welcomes all forms of contributions. Contributors to the project should read over the contribution docs for more information.
We'd love to hear from you. Drop us a line at [email protected], visit our forum or contact form, or follow us on Twitter to stay informed of updates and news.
関連プロジェクトを探す
Asabeneh/30-Days-Of-Python
30 Days of Python プログラミングチャレンジは、Python プログラミング言語を 30 日で学ぶためのステップバイステップのガイドです。このチャレンジは 100 日以上かかることもあります。自分のペースで進めてください。こちらの動画も役立つかもしれません: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
78,691 スターgrafana/grafana
オープンで組み合わせ可能なオブザーバビリティおよびデータ可視化プラットフォームです。Prometheus、Loki、Elasticsearch、InfluxDB、Postgres など、複数のソースからメトリクス、ログ、トレースを可視化できます。
77,876 スターredis/redis
リアルタイムのデータ駆動型アプリケーションを構築する開発者にとって、Redis は最も選ばれ、最速で、機能が最も豊富なキャッシュ、データ構造サーバー、ドキュメントおよびベクトルクエリエンジンです。
77,489 スターapache/superset
Apache Superset は、データ可視化とデータ探索のためのプラットフォームです。
75,513 スター