Arrays subsume tables, with multiple data modelings that can be tailored to your application for maximizing performance. Dense vector: Slice on row ID as non-materialized integer dimension.
Dense and sparse multi-dimensional arrays are able to efficiently capture all types of data, for any current and future data workload.
With the ability to model data using various dimensions, configurable tiling and a variety of layouts on the storage medium, TileDB Embedded is a versatile, yet super performant, storage engine, ideal for any application. TileDB Embedded is currently used in a broad spectrum of industries, including healthcare, telecommunications, defense, finance, earth observation and many more.
INTEROPERABILITY
APIs and integrations
Choose from a growing set of language APIs, popular data science tools and research workflows.
Applications
SQL
Distributed Computing
ML & Data Science
APIs
# Pip:
pip install tiledb
# Or Conda:
conda install -c conda-forge tiledb-py
USAGE