TileDB EmbeddedThe universal storage engine
Any dataAny backendAny tool
The need for a universal storage engine
Files and multiple formats compromise performance and scale
The challenge
- A sea of files and legacy formats
- Formats not designed for the cloud
- Data conversion before analysis
- Data updates hard to handle
The solution
- Multi-dimensional arrays
- Cloud-native format
- Interoperability with zero-copy
- Built-in data versioning
Store and access any data in a single format
A powerful engine architected around multi-dimensional arrays
TileDB Embedded is the only storage engine architected around dense and sparse multi-dimensional arrays, which can model any data, such as dataframes, genomic variants, images, video and many more. It is open-source under the MIT License.
See TileDB Embedded use-cases
Superior performance
TileDB Embedded exhibits superb performance for both dense and sparse array storage and access. Slice from any backend in an out-of-core fashion, and optimize operations via parallel IO, compression, and encryption.
Rapid updates and data versioning
TileDB Embedded provides rapid updates embracing immutability, ideal for cloud object stores. This further allows data versioning and time traveling, which are important for data science and applications that require auditing ability.
Extreme interoperability
TileDB Embedded is built in C++ and exposes multiple different language APIs, such as C, C++, Python, R, Java, and Go. It also includes integrations with distributed compute frameworks such as Spark and Dask, SQL engines (MariaDB and PrestoDB), and geospatial libraries (PDAL and GDAL).
Optimized for the cloud
TileDB Embedded is built with cloud object store challenges in mind, such as eventual consistency. It supports AWS S3, Google Cloud Storage and Azure Blob Storage. Any TileDB array works in an identical manner whether it is stored locally or on the cloud.
TileDB advantage
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| Features | |||
| Dense N-dimensional |  | | |
| Sparse N-dimensional | |  | |
| Dataframe support | | | |
Flexible layouts | | | |
| Arbitrary indexing | | | |
| Data versioning | | | |
| Time traveling | | | |
| Cloud-native | | | |
| Multiple APIs | | | |
Resource center
Join the growing TileDB Embedded open-source community on GitHub and shape the future of data management.
Documentation
TileDB Embedded is a deep technology. There is a lot more to explore. Get started with our docs and check back for updates.
Forum
Your use cases are shaping TileDB as the universal storage engine. Join the discussions on the TileDB forum.
Join the conversation
We invite you to participate in our Slack Channel. Come up with questions, get answers and become a part of the TileDB Community.
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