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Model any complex multi-dimensional data as arrays. Dataframes, genomic variants, satellite images or time-series, can all be efficiently represented as dense or sparse arrays. TileDB implements a universal array format that captures all data science applications.
TileDB is built with cloud object store challenges in mind and delivers superior performance via an optimized protocol and parallel IO. TileDB works on AWS S3, Google Cloud Storage and Azure Blob Storage.
TileDB offers numerous APIs (C, C++, Python, R, Java, Go) and integrations (PrestoDB, MariaDB, Dask, Spark, PDAL, GDAL), eliminating data conversions with zero-copying wherever possible.See all API Integrations
>>> import tiledb >>> array = tiledb.open("s3://tiledb-inc-demo-data/2.0/example") >>> array.shape (100, 100, 30) >>> array.dtype dtype("float64") >>> np.mean(array[:,:,1:10]) 0.49943713803540135
TileDB supports data versioning with rapid updates and time traveling, all built into its cloud-native array data format and storage engine.