Side by side
Daft vs dplyr
Both stand on data transformation tools. Which one you can start free with, which one lets you read the code, and what each costs once you pay.
Free plan LinuxMac
Choose Daft if you need a free, code-driven engine for AI workloads across structured data and media, with local execution and distributed scaling options. Consider the Dashboard security limit when deciding how to deploy it, especially if the Dashboard could be reachable from the public internet.
Visit Daft Free plan LinuxMacWindows
dplyr provides a focused set of code-based operations for transforming and grouping data, with additional verbs for multiple tables. Its documented backends extend its use to relational databases and several larger-data settings.
Visit dplyrThe facts
| Daft | dplyr | |
|---|---|---|
| Free plan | Yes | Yes |
| Open source | Not published | Not published |
| Runs on | Linux, Mac | Linux, Mac, Windows |
| Lowest paid plan | Free or on request | Free or on request |
| Plans published | 1 | 1 |
| Maker | Not published | Not published |
| Website | daft.ai | dplyr.tidyverse.org |
| On data transformation tools | #10 of 37 | #14 of 37 |
Daft: what it does well
- One Python API handles images, audio, video, text, and structured data.
- Includes prompts, embeddings, and zero-shot classification operations.
- Can scale from local execution to Ray or Kubernetes deployments.
- Documents multiple storage, table, catalog, and AI provider integrations.
- Free to use and self-hosted.
What to know first
- Requires Python 3.10 or higher.
- Supports Linux and macOS platforms.
- The Dashboard has no built-in authentication.
dplyr: what it does well
- Free package with an MIT license.
- Core verbs cover common data transformations.
- group_by() supports grouped operations.
- dbplyr translates code to SQL.
- Available for Linux, macOS, and Windows.
What to know first
- CRAN package requires R 4.1.0 or later.
- Transformations use a code-based interface.
- Listed formats are data frames and tibbles.