Alteryx Designer vs data.table
Alteryx Designer
alteryx.comdata.table
rdatatable.gitlab.ioSide by side
| Figure | Alteryx Designer | data.table |
|---|---|---|
| Price from | $250/mo | Free |
| Free plan | — | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | — | Yes |
| API | Yes | — |
| Plans published | 4 | 1 |
| Spec score · Data Transformation Tools | 8.5 (#10) | 8.5 (#11) |
| Integrations | The product page says Designer integrates with 80+ data sources and outputs to over 70 tools, with native cloud connectors such as Snowflake and Databricks. | data.table is an R package and can use R functions from other packages in queries. |
Plans
Alteryx Designer
- Starter Edition$250 a month
- Starter EditionPriced on request
- Professional EditionPriced on request
- Enterprise EditionPriced on request
In their own words
Alteryx Designer
Alteryx Designer brings data preparation, blending, and predictive, statistical, and spatial analytics into a visual workflow environment. Users arrange drag-and-drop tools on a canvas that records each analysis step; the product page describes more than 300 automation tools. Its low-code and no-code capabilities cover spatial and prescriptive analytics, as well as extracting insights from PDFs, text files, and images. Ask Alteryx can build workflows from natural-language requests, and the AI Tool Palette can add LLMs to workflows. The product page lists connections to more than 80 data sources and outputs to over 70 tools, including cloud connectors such as Snowflake and Databricks. SDKs let users add custom tools and formulas using multiple programming languages. Designer Desktop requires Windows; macOS use is listed through a virtual machine. A separate Designer Cloud runs in a browser with current Chrome, Edge, or Firefox. Starter Edition costs $250 a month, billed annually, for 1–10 seats, cloud-only use, and CSV, XLSX, and JSON file sources.
data.table
data.table is a free R package providing a high-performance version of base R’s data.frame. Its code interface supports filtering, grouping, aggregation, ordered and rolling joins, overlapping and non-equi joins, reshaping with dcast and melt, and adding, updating, or deleting columns. fread() reads delimited text, including CSV, TSV, compressed .gz and .bz2 files, and can source web URLs or shell commands. fwrite() writes delimited files with an emphasis on speed for large files. Many operations use multiple CPU threads internally. Columns can be changed by reference without copies, and the project reports no external Imports, LinkingTo, or Depends dependencies. Queries can call R functions from other packages. data.table runs on Linux, macOS, and Windows and requires base R. It is self-hosted and licensed under MPL-2.0. The project’s stated scope excludes binary formats such as Parquet and data stored on disk or in remote SQL databases.