Kyvos vs Synmetrix

Kyvos is a semantic layer for enterprise AI and business intelligence that gives analytics tools shared metrics, definitions, and business logic. Kyvos says it delivers sub-second analytics across massive datasets and thousands of concurrent users. Listed BI connections include Tableau, Power BI, Excel, Strategy, and Looker; the data ecosystem includes Snowflake, Databricks, BigQuery, AWS, Redshift, Azure, Google Cloud, and Microsoft Fabric. Deployment options include cloud marketplaces, managed service, and on-premises environments, with a hybrid deployment model. Controls include role-based access and row- and column-level security. Kyvos also lists HIPAA and PCI support, high availability, and disaster recovery. Its security policy describes annual SOC 2 Type 2 audits and encryption at rest with AES 128-bit or better and in transit with TLS 1.2 or better. There is no free plan, but the trial includes $500 in Kyvos credits, described as approximately 820 core-hours. Cloud marketplace use costs $0.41 a month, billed per core hour; managed service costs $0.61 a month, also billed per core hour.

Synmetrix is an open-source data engineering platform and semantic layer for defining and sharing organizational metrics from a central model. It uses Cube data models to define metrics and dimensions, then applies transformations and aggregations so applications can use consistent definitions. The maker says it connects to more than 50 data sources and can integrate with any BI tool. Users can explore metrics in its interface or distribute the model through a SQL API to BI tools, dashboards, reports and data science consumers. Model versioning and branching track changes, while query logs, caching and pre-aggregations support data workflows. Role-based access controls govern access to models and metrics; the project also describes upstream data controls for shared security and governance. Synmetrix supports scheduled reports and configurable alerts, with reports deliverable by email, Slack or webhooks. The core is Apache License 2.0 and the platform is intended for self-hosted, including on-premise, deployment. Setup uses Docker and Docker Compose with PostgreSQL. Listed hardware requirements are a 3.2 GHz or faster processor, at least 8 GB RAM and at least 30 GB free disk space.