TileDB is an open-source multi-dimensional arrays Database
Table of Content
TileDB is a versatile and high-performance engine designed for managing both dense and sparse multi-dimensional arrays. It serves as an efficient solution for modeling complex datasets across various domains. It is built as an embeddable C++ library, TileDB operates seamlessly on Linux, macOS, and Windows platforms.
TileDB is widely used across numerous industries due to its ability to handle diverse data types and structures. For instance, in genomics, TileDB enables efficient storage and querying of large-scale genomic datasets, which are often multi-dimensional in nature.
In the geospatial domain, it supports advanced spatial indexing and analysis of satellite imagery, geographic information systems (GIS), and point cloud data.
In finance, TileDB helps manage time-series data, such as stock market trends, transaction records, and risk modeling, where high performance and scalability are critical.
Hazem Abbas
The strength of TileDB lies in its ability to represent virtually any dataset as dense or sparse multi-dimensional arrays—a format that aligns well with the internal workings of most data science tools. By organizing your data and metadata into TileDB arrays, you eliminate the complexities associated with traditional data storage and management.
This approach not only simplifies workflows but also ensures optimal performance when accessing and analyzing data using your preferred data science frameworks and applications.
Features
- Data Organization : Workspaces and teamspaces for asset ingestion, organization, and management.
- Optimized Structures : Multi-dimensional dense and sparse arrays, dataframes, and key-value stores (via sparse arrays).
- Cloud-Native : Seamless integration with AWS S3, Google Cloud Storage, and Azure Blob Storage.
- Efficient Storage : Chunked (tiled) arrays with compression, encryption, checksum filters, and parallel I/O.
- Versioning : Data versioning for rapid updates and time-travel capabilities.
- Metadata & Grouping : Support for array metadata and array groups.
- Multi-Threading : Fully multi-threaded implementation for high performance.
- Collaboration : Secure cross-team data sharing with compliance to major regulatory frameworks.
- Analysis Tools : Pre-built workflows, Jupyter notebooks, and customizable dashboards for data analysis and modeling.
- Extensibility : Numerous APIs (C++, Python, R, Java, Go, etc.) and integrations (Spark, Dask, MariaDB, GDAL, etc.).
APIs
The TileDB team maintains a variety of APIs built on top of the C++ library:
Integrations
TileDB is also integrated with several popular databases and data science tools:
Install
# Conda (macOS, Linux, Windows):
$ conda install -c conda-forge tiledbInstall Using Docker
$ docker pull tiledb/tiledb
$ docker run -it tiledb/tiledbLicense
The project is open-source, released under the permissive MIT License, and is actively developed and maintained by TileDB, Inc.
To differentiate this core offering from other products in the TileDB ecosystem, it is commonly referred to as TileDB Embedded.
Resources & Downloads
TileDB-Inc
