Sema vs Synmetrix
Sema
semalayer.comSynmetrix
synmetrix.orgSide by side
| Figure | Sema | Synmetrix |
|---|---|---|
| Price from | $49/mo | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 4 | 1 |
| Spec score · Semantic Layer Software | 8.7 (#4) | 8.4 (#8) |
| Deployment | Sema says it can run in the customer’s VPC or its own environment; its self-hosted Kubernetes deployment uses a Helm chart and customer-provided Postgres and object storage. | Synmetrix is described as self-hosted and can be deployed using Docker Compose with a Postgres database. |
| Integrations | Sema describes its capabilities as MCP tools for use with Claude, Cursor, or an in-house agent, and supports OAuth2/OIDC identity providers including Okta, Entra, Auth0, and Google Workspace. | The maker says Synmetrix connects to more than 50 data sources and can integrate with any BI tool. |
| Product | Sema is a semantic layer for enterprise AI that connects databases, infers data meaning, and answers business questions in plain English with governance. | Synmetrix is an open source data engineering platform and semantic layer for centralized metrics management. |
| Reports and alerts | Users can save and schedule reports for email delivery, and create scheduled threshold or deviation alerts on metrics. | It supports scheduled reports and configurable alerts that notify users about metric changes. |
| Security | Sema says it uses TLS in transit and encryption at rest, role-based access, restricted-column masking, workspace isolation, and an append-only log of queries, plans, and configuration changes. | The site describes upstream data access controls for uniform security and governance, and lists role-based access control. |
| Support | The Pro plan includes email support, Business includes priority support, and Enterprise includes a named customer success manager. | The project lists its documentation, Slack community, and GitHub for help, discussion, and bug reports. |
| What it does | Sema is a governed semantic layer that connects databases, models business meaning and answers questions in plain English with audit evidence. | Synmetrix is an open-source data engineering platform and semantic layer for centrally modeling, integrating, transforming, aggregating, and distributing metrics. |
Plans
In their own words
Sema
Sema is a semantic layer for enterprise AI that connects databases and answers business questions in plain English, with governance controls. It maps tables, joins, metrics, and business terms into a typed graph; verified inferred joins can be reused in later answers. It can ask clarifying questions, show the SQL and graph nodes behind an answer, and select a chart. Users can save and schedule reports for email delivery and set metric alerts for thresholds or deviations. Available connectors include PostgreSQL, MySQL, MariaDB, SQLite, and SQLAlchemy URIs; ClickHouse and Amazon Redshift are in beta, while SQL Server, Snowflake, BigQuery, Databricks, and dbt metadata are on the roadmap. Sema can run in a customer VPC or its own environment; self-hosting uses Kubernetes and Helm with customer-provided Postgres and object storage. The free Sandbox costs nothing and limits use to one connector, one user, 100 monthly chat queries, and five saved reports, without scheduled delivery or alerts. Pro costs $49 a month per user, with a three-seat minimum and a 14-day trial.
Synmetrix
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.