Databox vs LabPlot
Databox
databox.com
LabPlot
labplot.orgSide by side
| Figure | Databox | LabPlot |
|---|---|---|
| Price from | $6.58/mo | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| iOS | Yes | — |
| Android | Yes | — |
| API | Yes | — |
| Plans published | 7 | 1 |
| Spec score · Data Visualization Software | 9.2 (#4) | 8.1 (#39) |
| Free plan | Yes | Yes |
| Support | The listed plans include chat and email support. | Users can report bugs through KDE Bugtracking or the app, ask questions on KDE Discuss or Matrix, and contact the support team by email. |
Plans
Databox
- FreeFree
- Analyst$71 a month
- Team Core$199 a month
- Team Scale$319 a month
- Agency$79 a month
- Agency$79 a year
- CustomPriced on request
In their own words
Databox
Databox brings performance metrics and business context together for teams and agents to analyze, report on and act on results. Its AI Analyst answers plain-language questions using metrics, goals and historical business data. Teams can use shareable dashboards and scheduled reports, and share performance with people who do not have a login. Databox connects to more than 130 tools, as well as databases, spreadsheets and APIs; examples include Google Analytics 4, HubSpot, Google Sheets and Facebook Ads. The company says its integrations include more than 4,000 curated metrics. Agents and routines can automate recurring analysis and workflows under user oversight. The cloud service runs on the web and offers an API, hourly refreshes, embedded analytics and natural-language queries. Free includes one user, three data sources, one dashboard and report, and 50 AI credits per month; its maximum sync frequency is daily. Analyst, Team Core and Team Scale list hourly maximum sync frequency. Free is available, with a 14-day trial and paid plans from $71 a month billed annually. Databox describes its audience as growing businesses, agencies and AI implementers. Its security practices include encryption at rest and in transit, access controls, and a statement that data is not used to train AI models.