Strata
Strata gives data teams a governed semantic layer, self-service dashboards, and AI analytics agents for exploring warehouse data. Its federated routing sends queries to suitable OLAP tiers, with warehouse fallback when needed.
One of 181 tools in Business Intelligence
Who it's for
- Data teams defining shared measures and dimensions in YAML and validating the model against a warehouse.
- Business intelligence teams giving non-technical users governed self-service access to reports and dashboards.
- Teams building analytics agents that need to query live measures and dimensions while inheriting model-defined row-level security.
How it fits your workflow
Define the semantic model in YAML using Strata's naming conventions. The page says a coding agent can draft it, Strata audit validates it against the warehouse, and Git carries it to production.
Build dashboards or agents in the shared editor. Users can explore the model, combine facts at a common grain, and use measures and segments; semantically invalid queries are refused.
Queries go through the semantic layer and are routed to an OLAP engine or warehouse tier that can answer them. The page names ClickHouse and Druid as hot-tier engines, Snowflake as warm, and AWS Athena as cold.
Pricing
Free: The page offers “Try it free,” but does not provide plan details or pricing amounts.
The vendor doesn't publish prices. Check with Strata directly.
Prices checked on Oct 1, 2026 from the vendor's site. They can change; confirm before you buy.
Key features
- Semantic layer as code
- Define the model using two YAML file types and a naming convention. A coding agent can draft the model, and Strata audit validates it against the warehouse before Git carries it to production.
- Dynamic universes
- People and agents can explore the whole model without first selecting a view, explore, or cube. The page says steps are validated and previewed as users build, and semantically invalid queries are refused before running.
- Automatic cross-domain blending
- Strata aggregates facts to a common grain and joins them on conformed keys rather than joining fact tables directly. The page says this prevents double counting and allows the system to refuse an agent request rather than return a wrong number.
- Federated smart OLAP routing
- Queries are routed to the fastest engine that can answer them, with a fallback to the warehouse when filters fall outside the hot tier. The page describes partition- and aggregate-aware routing across hot, warm, and cold tiers.
- Self-service dashboards
- Dashboards use a layout engine that sizes, places, and colors views based on their order, without requiring users to arrange them on a grid.
- Measures and segments
- Strata supports Standard, Complex, Snapshot, Exclusion LOD, and Inclusion LOD measure types, plus segments that can show a cohort beside a baseline.
Works with
- ClickHouse and Druid
- Snowflake
- AWS Athena
- Google Sheets
- MCP
Alternatives to consider
-
Omni
Choose it if you want an AI-first analytics platform that also lists spreadsheets and embedded analytics among its capabilities.
-
Supaboard
Choose it if your analytics workflow specifically needs alerts and board-ready presentations from AI analysts.
Getting started
Docker and your own coding agent; the page says to run Strata on your machine.
- Start Strata on your machine with Docker and your coding agent; the page describes setup to insights in 15 minutes.
- Draft the semantic model using the two YAML file types and naming convention.
- Validate the model against the warehouse with Strata audit.
- Use Git to carry the validated model to production, then create reports or agents.