BigML
7.7#1 in predictive analytics softwareFrom $10,000 a yearFree planWebAPImacOSSelf-hosted
VisitBigML vs Pecan AI
What both publish
| Fact | BigML | Pecan AI |
|---|---|---|
| Deployment | Private deployments can run on a preferred cloud provider, ISP, or on-premises behind a corporate firewall, as managed or self-managed deployments. | Users can schedule recurring predictions and send them to databases, data warehouses, CRMs, or other systems. |
| Founded | 2011 | 2018 |
| Headquarters | BigML lists Corvallis, Oregon as headquarters and Valencia, Spain as its European headquarters. | Tel Aviv, Israel |
| Integrations | Official tools include Google Sheets, Zapier, Node-RED, Alexa, PredictServer and a native BigMLX macOS application. | Built-in integrations include Snowflake, Databricks, BigQuery, Salesforce, HubSpot, Redshift, PostgreSQL, Oracle, MySQL, and other data sources. |
| Security | BigML states that connections use HTTPS, resources are private by default, and staff cannot access customer data without explicit consent. | Pecan states that it is ISO 27001 certified and undergoes an annual independent SOC 2 Type II assessment. |
| 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 listed plans include in-app support, with Essential enablement on Team and Pro enablement on Business. |
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
Pecan AI plans
- BusinessPriced on request
- StarterPriced on request
- TeamPriced 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 Pecan AI if…
It suits data and business teams in marketing, sales, operations, customer success, and finance. The no-code workflow is aimed at analysts who need predictive models without a data science degree.