Amazon SageMaker Lakehouse vs IOMETE

Amazon SageMaker Lakehouse has no write-up on Specifiction yet; its figures are above.

IOMETE is a data lakehouse platform for AI and analytics built on Apache Spark, Apache Iceberg, and Kubernetes. It supports SQL analytics, ACID transactions, streaming ingestion, and open table formats, with external storage. Its Query Federation Engine can query relational and NoSQL databases and flat files without complex ETL pipelines. A centralized catalog holds dataset metadata, lineage, collaboration, and quality information. Teams can connect through JDBC/ODBC, REST APIs, SQL interfaces, custom endpoints, and webhooks. Integrations include Tableau, Power BI, and Apache Superset for business intelligence, as well as Apache Airflow, dbt, and Apache NiFi for data integration. Collaboration tools include a SQL editor, Git integration for SQL worksheets and queries, and multi-domain support. Access enforcement can operate at database, table, column, and row levels, with masking and row filters; authentication supports local credentials, LDAP synchronization, and federated SAML/OIDC. Deployment options include on-premises, private or public clouds, and hybrid environments. The Free plan allows up to 100 vCPUs and includes community support. Enterprise is listed at $500 per vCPU per year with a $100,000-per-year minimum commitment. Business Critical has a $250,000-per-year minimum commitment.