Tabular data is one of the most prevalent data types across all industries, but formatting it as CSV and Parquet files, and resorting to storing them in data lakes and cloud object storage as flat files, leads to extra data wrangling and management hassles.
Add flexibility to your dataframe analysis with open-source, cloud-native TileDB arrays. With the multi-dimensionality of TileDB, you can effectively index on more than one column in order to boost performance on multi-attribute queries. TileDB supports popular languages like Python and R, with convenient accessor functions that integrate with existing dataframe tools.
TileDB is designed for extreme performance on cheap cloud object storage, eliminating the need for in-memory engines like Apache Spark and external query cluster services like Presto and Trino.
Take advantage of secure data governance and serverless computation with TileDB Cloud. Extensive integrations allow you to use hosted Jupyter environments and TileDB Cloud UDFs to process large-scale workflows, while continuing to use popular tools like Pandas and Apache Arrow. Enjoy extreme, scalable performance while minimizing your TCO.