BigML
7.7#1 in predictive analytics softwareFrom $10,000 a yearFree planWebAPImacOSSelf-hosted
VisitBigML vs WEKA Data Platform
WEKA Data Platform
5.6#17 in low-code machine learning platforms softwareWebAPILinuxSelf-hosted
VisitWhat both publish
| Fact | BigML | WEKA Data Platform |
|---|---|---|
| Company founding | BigML says it was founded in January 2011. | WEKA's company story says it set out in 2013 to build its product. |
| Deployment | Private deployments can run on a preferred cloud provider, ISP, or on-premises behind a corporate firewall, as managed or self-managed deployments. | WEKA describes deployment across edge, on-premises, hybrid-cloud, and multicloud environments. |
| Founded | 2011 | 2013 |
| Headquarters | BigML lists Corvallis, Oregon as headquarters and Valencia, Spain as its European headquarters. | Campbell, California, United States |
| Security | BigML states that connections use HTTPS, resources are private by default, and staff cannot access customer data without explicit consent. | WEKA describes end-to-end encryption with FIPS 140-3 Level 1 and integrated key management for data at rest, in motion, and in the cloud. |
| 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 AWS Marketplace listing directs customers to WEKA's Support Portal or email for support. |
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
WEKA Data Platform plans
- WEKA Data Platform [Private Offer Only]Priced 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 WEKA Data Platform if…
It suits teams handling demanding data workloads across on-premises and cloud environments, including AI/ML, life sciences, engineering, and HPC. Organizations seeking unified access protocols, snapshot protection, or Kubernetes management may also find its listed capabilities relevant.