BigML
7.7#1 in predictive analytics softwareFrom $10,000 a yearFree planWebAPImacOSSelf-hosted
VisitBigML vs JADBio
What both publish
| Fact | BigML | JADBio |
|---|---|---|
| API | BigML exposes a REST API that covers most Dashboard functionality and authenticates requests with a username and API key over HTTPS. | The REST API can add AutoML, including image analysis, to applications and automate workflows; a Python client is offered through GitHub, PyPI, and Anaconda. |
| Deployment | Private deployments can run on a preferred cloud provider, ISP, or on-premises behind a corporate firewall, as managed or self-managed deployments. | Business Pro lists AWS container and on-premise delivery options in addition to SaaS. |
| Founded | 2011 | 2019 |
| Headquarters | BigML lists Corvallis, Oregon as headquarters and Valencia, Spain as its European headquarters. | Heraklion, Crete, Greece; Los Angeles, California, US |
| Integrations | Official tools include Google Sheets, Zapier, Node-RED, Alexa, PredictServer and a native BigMLX macOS application. | The Team plan includes connection to public repositories, while Business Pro plans include connection to public and private repositories. |
| Support | BigML Lite includes standard 8x5 email and chat support with a 48-hour maximum response time; Enterprise lists customized email and chat with a 24-hour maximum response time. | The pricing page lists Standard, Premium, and Platinum support service levels, with Platinum listed for Business Pro. |
BigML plans
- FREEFree
- Basic BigML training$800, paid once
- BigML Lite$1,000 a month
- Extra Support$3,000 a month
- BigML Lite (annual)$10,000 a year
- Bronze Enterprise$45,000 a year
JADBio plans
- BasicFree
- Team$2,199
- Business ProPriced on request
Pick BigML if…
BigML suits analysts, software developers, and scientists who need machine-learning tools, workflow automation, or model deployment options. Its API and language bindings may suit teams integrating models into software.
Pick JADBio if…
JADBio is aimed at life scientists, research institutions, biotech and pharmaceutical companies, and other scientists working with study or public data. Its no-code approach may suit users seeking predictive analysis without building an ML workflow from scratch.