It is our vision to make TileDB Embedded interoperable with every popular SQL engine and data science tool. We have already built and continue to maintain numerous integrations, which we describe here.

Distributed computing

Connectors to distributed computing frameworks that allow you to scale out your computations on TileDB arrays.

• Spark:

  • Code: https://github.com/TileDB-Inc/TileDB-Spark​

  • Docs: https://docs.tiledb.com/spark/​

• Dask:

  • Code: https://github.com/dask/dask/blob/master/dask/array/tiledb_io.py​

  • Docs: https://docs.tiledb.com/dask/​

SQL engines

Connectors to popular databases that allow you to perform efficient SQL queries on TileDB arrays, even when they are stored on cloud object stores like AWS S3, GCS and Azure.

• PrestoDB:

  • Code: https://github.com/TileDB-Inc/TileDB-Presto​

  • Docs: https://docs.tiledb.com/prestodb/​

• MariaDB:

  • Code: https://github.com/TileDB-Inc/TileDB-MariaDB​

  • Docs: https://docs.tiledb.com/mariadb/​

Geospatial

Connectors to popular geospatial tooling that allows you to operate directly on data stored as TileDB dense or sparse arrays.

• PDAL: https://github.com/PDAL/PDAL/tree/master/plugins/tiledb/io​

• GDAL: https://github.com/OSGeo/gdal/tree/master/gdal/frmts/tiledb​

• Rasterio: https://github.com/mapbox/rasterio/pull/1729​

• SAR: https://github.com/TileDB-Inc/TileDB-SAR​

• Docs: https://docs.tiledb.com/geospatial/​

Genomics

A powerful variant store solution built on TileDB core with sparse arrays.

• TileDB-VCF:

  • Code: https://github.com/TileDB-Inc/TileDB-VCF​

  • Docs: https://docs.tiledb.com/main/solutions/integrations/population-genomics​