Delve vs spaCy
Delve
delvetool.comspaCy
spacy.ioSide by side
| Figure | Delve | spaCy |
|---|---|---|
| Price from | $16.67/mo | Free |
| Free plan | — | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| Self-hosted | — | Yes |
| Plans published | 3 | 1 |
| Spec score · Text Analytics Software | 8.1 (#8) | 8.4 (#4) |
| Headquarters | New York, NY, United States | Berlin, Germany |
| Purpose | Delve is cloud-based qualitative data analysis software for coding research data and finding insights from interviews and focus groups. | spaCy is a Python library for advanced natural language processing, designed for production use and processing large volumes of text. |
| Security | Delve states that data is encrypted in transit with TLS and at rest by its database subprocessors, and that accounts support two-factor authentication. | The official pages opened for this research did not state a security certification or compliance standard. |
Plans
Delve
- Education monthly$18 a month
- Standard monthly$50 a month
- Education annual$200 a year
In their own words
spaCy
spaCy is a free, open-source Python library for building natural language processing applications, with a focus on production use and large volumes of text. Its components handle named entity recognition, part-of-speech tagging, dependency parsing, sentence segmentation, text classification, lemmatization, morphology, and entity linking. The project lists support for 75+ languages and 84 trained pipelines for 25 languages, though trained pipelines are not available for every language. Developers can configure and train custom pipelines, describe training runs with configuration files, and package pipelines for installation as Python packages. spaCy can use pretrained transformers through spacy-transformers, and supports custom models in PyTorch, TensorFlow, and other frameworks. spaCy Projects supports workflows for downloads, commands, checksum verification, and caching, along with integrations for tracking, demos, model serving, distributed training, and Hugging Face Hub. Installation is available through pip, conda, or source on Linux, macOS, and Windows. The library can run on a user's servers without data leaving them. It is not a hosted software-as-a-service product or web application. The library is free under AGPL or a commercial license; transformer models require a GPU to run effectively.