PRODUCT COMPARISON
H2O-3 Secure vs
Open Source
One product. Two paths. Pick the one that fits how you run H2O-3.
Which is right for you?
H2O-3 OSS
FREE. APACHE 2.0. OPEN SOURCE
- Comfortable managing upgrades, patches,and operations yourself
- Not dependent on H2O-3 for production outcomes
H2O-3 Secure
COMMERCIAL. SUPPORTED. PRODUCTION-GRADE.
- FedRAMP High-aligned designed for audit-sensitive AI/ML workloads
- Audit-supporting capabilities for SOC 2, ISO 27001, ISO 42001
- Commercial CVE patching
Keep everything you have. Seamless upgrade.
Your code, APIs and pipelines run unchanged.
Proven ROI and Top Use Cases
Fraud detection
A U.S. based payments company used H2O for real-time merchant fraud detection across a dataset of 160 million records and 1,500 features.
$1M in monthly savings for every 1% reduction in fraud.
Customer churn prediction
A global digital payments company used H2O with Random Forest and GBM models to predict customer churn and improve customer retention and reactivation programs. .
Model training and scoring cut from days to minutes.
Marketing response optimization
A large marketing services provider used H2O ML models to improve direct marketing campaigns. The effort produced a 3–5% lift response rates, adding 15K new customers.
$9M in incremental revenue from a single campaign.
WHY THIS MATTERS NOW
Self-managed AI/ML in production puts the operational and audit burden on your team
The same algorithms creating real value are often running on unsupported software. These are examples of operational and governance considerations organizations commonly evaluate under frameworks such as SOC 2, ISO 27001, and ISO 42001:
- Self-managed OSS leaves SLAs, incident response, and remediation timelines to your team.
- Unpatched vulnerabilities that may be identified during audits under frameworks such as SOC 2 and ISO 27001, particularly where organizations cannot demonstrate effective vulnerability management and vendor oversight.
- Increased burden on internal teams to establish and evidence supportability, lineage, and change-management controls for auditors, regulators, and stakeholders.
- A widening gap against ISO 42001 and emerging AI governance frameworks that emphasize oversight, traceability, and lifecycle management of AI systems.
Your CISO, auditor and board are already asking about this. H2O-3 Secure is the supported, auditable operating model that answers them.
H2O-3 Secure does not make an organization SOC 2 or ISO compliant by itself. It strengthens the controls evaluated during audits.
AT A GLANCE
What H2O-3 Secure Features
H2O-3 Secure is a seamless upgrade from H2O-3 OSS — your code, APIs and pipelines run unchanged.
H2O-3 OSS
Apache 2.0
| H2O-3 Secure
Commercial License
| |
|---|---|---|
| All H2O-3 algorithms | ✓ | ✓ |
| H2O AutoML | ✓ | ✓ |
| Multi-node distributed model training | ✓ | ✓ |
| Model scoring | ✓ | ✓ |
| PyPi and R-CRAN packages | ✓ | ✓ |
| Community support | ✓ | ✓ |
| Early access to latest algorithms and improvements | ✓ | |
| Hadoop and Kubernetes enterprise packages | ✓ | |
| Production MOJO model scoring for Hadoop, Spark, Teradata, Oracle | ✓ | |
| Managed distributed XGBoost service | ✓ | |
| Model reproducibility | ✓ | |
| Automated model documentation (H2O Auto Doc) | ✓ | |
| Enterprise SSO & secrets management* | ✓ | |
| RBAC and audit-ready controls (SOC 2, ISO 27001, ISO 42001)* | ✓ | |
| FedRAMP High-aligned | ✓ | |
| Premium support with SLAs | ✓ | |
| Commercial CVE patching & long-term support | ✓ | |
| Enterprise roadmap visibility & early access | ✓ |
*Available in H2O.ai AI Cloud deployments
H2O-3 Secure extends H2O-3 OSS your teams already trust — with the multi-node deployment, governance, and audit controls required to run AI in production.
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FedRamp
Microsoft Azure
Amazon Web Services
Ready to move H2O-3
on to a supported path?
Schedule a 30-minute Production Review. We'll assess your H2O-3 deployment, support needs, and compliance posture, then map the shortest path to a production-grade, auditable operating model.