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.
You can install the TileDB C++ library as follows:
# Conda (macOS, Linux, Windows):
$ conda install -c conda-forge tiledb(see links below for Python, R, and other API installation instructions)
Alternatively, you can use the Docker image we provide:
$ docker pull tiledb/tiledb
$ docker run -it tiledb/tiledbWe include several examples. You can start with the following:
You can find the detailed TileDB documentation at https://docs.tiledb.com.
Please see building from source in the documentation.
The TileDB data format is open-source and can be found here.
- TileDB-BioImaging: TileDB library for biomedical imaging, with support for image-optimized compression using WebP.
- TileDB Geospatial Tools (GDAL, PDAL, Rasterio)
- 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.
The TileDB team maintains a variety of APIs built on top of the C++ library:
TileDB is also integrated with several popular databases and data science tools:
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.
