disy Cadenza vs H2O Driverless AI

disy Cadenza combines analytics, reporting, and location intelligence to support data-driven decisions across an organization. Users can create interactive dashboards with tables, charts, maps, indicators, images, and text, and refresh analyses when queried. Reports can be generated on a schedule or in response to events, then distributed to employees. For geospatial work, Cadenza maps and analyzes data, including temporal-spatial analysis with automated animations. It also offers AI-based analysis methods, automated insights, and forecasting. Users can upload Excel, CSV, Shapefile, KML, GeoPackage, and GPX files for self-service analysis. Connections include Oracle, PostgreSQL, Microsoft SQL Server, SAP HANA, Elasticsearch, WFS, WMS, ArcGIS Server REST, and WMTS; SAP HANA is identified as beta. Security features include fine-grained roles and privileges, access controls, LDAP and OpenID Connect authentication, and audit logging. Deployment options include on-premises, private cloud, or a hyperscaler, with container and Kubernetes operation described in documentation. Disy offers a fully functional trial package with documentation and tutorials, but registry download requires credentials from an account representative. Pricing is on request.

H2O Driverless AI automates machine-learning work from feature engineering and model building through validation, tuning, selection, visualization, interpretability, and scoring-pipeline generation. It explains model output at both global and individual-prediction levels. Models can be deployed as REST endpoints, cloud services, or optimized Java code for edge devices. Supported hardware includes NVIDIA GPUs, IBM Power 9, and Intel x86 CPUs; GPU-accelerated algorithms include XGBoost, TensorFlow, and LightGBM. Documented integrations include Kubernetes, Kubeflow, SageMaker, Alteryx, Jupyter/Python, KDB, Qlik, Trifacta, and UiPath. Data sources include HDFS, Amazon S3, Azure Blob Storage, Google BigQuery, Google Cloud Storage, Snowflake, JDBC, Databricks, and Delta Table. Cloud installation options are H2O AI Cloud, AWS, Azure, and Google Cloud. H2O offers a 21-day public-cloud evaluation license and a guided two-hour cloud test drive. Commercial licensing requires contacting sales; no price is listed. The default installation disables security, so production use calls for secure installation.