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TileDB Cloud

Serverless Data Science
GenomicsGenomicsArrow
GeospatialGeospatialArrow
DataframesArrow
Cloud_AWSCreated with Sketch.

Store any data as multi-dimensional arrays in a cloud-native, open-source format

Arrows
Cloud_tiledbCreated with Sketch.

Enjoy TileDB Cloud's elasticity and access control, without deployment hassles

Arrows
NotebooksNotebooks
IntegrationsIntegrations
ServerlessServerlessCreated with Sketch.
Sign upDocs
GenomicsGenomicsArrow
GeospatialGeospatialArrow
DataframesArrow
Cloud_AWSCreated with Sketch.

Store any data as multi-dimensional arrays in a cloud-native, open-source format

Arrows
Cloud_tiledbCreated with Sketch.

Enjoy TileDB Cloud's elasticity and access control, without deployment hassles

Arrows
NotebooksNotebooks
IntegrationsIntegrations
ServerlessServerlessCreated with Sketch.
The Challenge
  • ✘Thousands of files
  • ✘Cumbersome sharing
  • ✘Deployment hassle
  • ✘Slow onboarding
The Solution
  • Arrays
    Universal array format
  • Collaboration
    Share easily with anyone
  • Serverless
    100% serverless
  • Jupyter
    Hosted notebooks in seconds

Explore the capabilities

Powerful arrays

Store any data as multi-dimensional dense or sparse arrays, the language of data science. The TileDB storage engine is open-source, supports data versioning built-in, comes with multiple APIs and interoperates with data science tooling.

Learn more

Easy sharing

No more file management and clunky catalogs. Share arrays with any number of users while retaining ownership of your own data. Log and track all usage.

Serverless SQL & task graphs

No more deploying clusters. Analyze your data with serverless SQL. Use task graphs to run parallel user-defined functions. Enjoy ease-of-use, superior scalability and performance while eliminating idle compute costs.

Explore Cloud API docs

Jupyter notebooks

Run Jupyter notebooks in seconds right from TileDB Cloud and jumpstart your work with examples on common use cases. Choose notebooks from multiple configurations and server sizes.

Pricing

Kickstart your analysis with minimal cost and scale automatically, paying only for what you use

Tasks
$0.11 / CPU / hour
Time taken for slicing an array, performing a SQL query or computing
a UDF task
Data
$0.14 / GB
Amount of data retrieved from the service to your client, not the data processed by queries
Notebook
$0.06 / CPU / hour
Time you spend running a Jupyter notebook server on the TileDB Cloud service

Pricing examples

Take a look at some pricing examples

Suppose you run a UDF which takes 300 seconds and returns no data to your client outside TileDB Cloud. Suppose also that the UDF uses 2 CPUs. You will then be charged:
  • Query time:(5 / 60) hours * 2 CPUs * $0.11 = $0.0183
  • Data retrieved:$0.00
  • Total:$0.02

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