Big data in your browser

Unmatched performance, stability and scalability.

Delivered inside the Datatailr platform, with our best-in-class encryption and data connectivity, all installed securely in your own cloud or on-prem account.

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Finally - your entire big data set, in your browser

Scales from local client side data sets, to remote server side data sets that are larger than memory.

No need to spend time cutting your data, or waiting for someone to build you a dashboard.

Connect, explore, test and ship your data. Yourself.

100% C++ that runs in a web browser & scales from local, client-side datasets to remote server-based datasets that are larger than memory.

The C++ Grid/Tree WebAssembly component delivers unmatched performance, stability and scalability.

dtcube pivot sum notional and sum quantity by trader

No loading time - instant viewing

Analyze and manipulate terabytes of data with multidimensional pivots, filters and custom columns.

Best-in-class developer experience

Enter any custom expression using any Polars functionality
Calculate anything you want
Server-side Python bindings - write a complete, fully-featured data model in less then 100 lines of code
Embed into any web-based solution; fully WebAssembly-based and entirely framework-agnostic

Excellent data aggregations and data-driven design

Visualize and build powerful dashboards
Aggregate, filter, slice and apply custom analytical functions
Dynamic runtime reconfiguration - pivot/filter/aggregate on large datasets at runtime
Sophisticated expression support, data-driven styling, expression-based filtering and alerts, column filters by text or histogram distribution
Report generation - results can be generated server side as pdf or excel reports

Configurable UI

Both vertical & horizontal trees support multi-dimensional pivots
Workflow integration - user defined buttons/checkboxes/dropdowns allow the cube to fire off custom actions and integrate with user's other applications

Connect to any data source

Use the Polars data model to load a CSV or parquet file, or connect to any source such as an s3 bucket, remote or local storage
Supply your own data model, or work with our team to write one in Python. Load from any database you want.
Stream live updates such as tick data
Polars data sources: https://docs.pola.rs/user-guide/io/

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