TileDB-Py
by TileDB-Inc
Python interface to the TileDB storage engine
AI summary
Data storage library
Provides a Python interface to store and manage large datasets in a distributed, columnar storage system.
- stars
- 190
- forks
- 33
- watching
- 29
Similar projects
Found by comparing what the projects do, not just their names.
Storage Manager Library
A Go interface to the TileDB storage manager
Columnar Storage Interface
A Java interface to a distributed columnar storage engine
Database interface
Provides an interface to the modern database TileDB from R.
Data storage API
Provides access to single-cell data at scale through a flexible, extensible API with storage and data access patterns
Storage library
C# bindings for TileDB Embedded storage engine
vector database
A serverless, scale-out vector similarity search and storage system with efficient database capabilities
Data storage library
A library providing a simple storage solution using stable memory, allowing canisters to store data without GC costs and upgradeability.
web2py/pydal500
Database Abstraction Layer
A pure Python Database Abstraction Layer that generates SQL/noSQL in real-time for different databases.
Bigtable client
Provides a Python interface to interact with Google Cloud Bigtable NoSQL database service.
Codec library
A Python implementation of a lightweight and efficient encoding and decoding program for blockchain data
Interface library
An interface to interact with Substrate nodes, enabling Python access to blockchain data and extrinsic execution.
Filesystem abstraction layer
Provides a unified interface to various filesystems and archives, abstracting the underlying storage technology.
pytorch/data1.1K
Data loader library
Provides scalable, performant data loading solutions and utilities to be shared by PyTorch domain libraries
gbif/pygbif114
Biodata API client
Provides a unified Python interface to the GBIF API for retrieving biodiversity data and accessing various datasets and resources.
Data Warehouse Library
A Python-based framework for transforming and analyzing unstructured data from various formats like images, audio, videos, text, and PDFs.
