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SPECIFICTION
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dbt Semantic Layer vs Miller

dbt Semantic Layer

getdbt.com

Miller

miller.readthedocs.io

Side by side

Figuredbt Semantic LayerMiller
Price from$0.09/moFree
Free planYesYes
Free trialYes—
Open source——
WebYes—
Windows—Yes
macOS—Yes
Linux—Yes
APIYes—
Self-hosted—Yes
Plans published51
Spec score · Data Transformation Tools8.9 (#8)7.6 (#25)
IntegrationsThe product page says the Semantic Layer offers an API, the dbt MCP Server, and dozens of out-of-the-box integrations for BI, notebooks, spreadsheets, embedded analytics, and AI systems.The documentation describes Miller as complementary to R, pandas, SQL databases, and the Unix toolkit.
Intended usersThe product is presented for data teams seeking governed, consistent metrics for analytics, embedded applications, and AI use cases.The author describes use across disciplines including DevOps, data science, and biology/genomics, while noting that many users focus on CSV.
PurposeThe Semantic Layer centralizes metric definitions on dbt models and automatically handles data joins for consistent use across downstream tools and applications.Miller is a command-line tool for querying, shaping, and reformatting data files in formats including CSV, TSV, JSON, JSON Lines, YAML, and DCF.
SupportThe pricing page lists 24x5 support for Starter and priority support with SLAs for Enterprise.The project directs users to GitHub Discussions for general questions, Stack Overflow for tagged questions, and GitHub Issues for bug reports and feature requests.

Plans

dbt Semantic Layer

  • DeveloperFree
  • dbt State add-on$0.09 a month
  • Starter$100 a month
  • EnterprisePriced on request
  • Enterprise+Priced on request

dbt Semantic Layer pricing →

Miller

  • MillerFree

Miller pricing →

In their own words

dbt Semantic Layer

The dbt Semantic Layer centralizes metric definitions on dbt models and handles joins so downstream tools and applications can use metrics consistently. MetricFlow generates SQL at query time from semantic model and metric configurations. Teams define those models and metrics in YAML as version-controlled, lineage-aware code. MetricFlow can optimize joins, rewrite queries to reduce compute and latency, and cache repeated queries. The product offers an API, the dbt MCP Server and integrations for BI tools, notebooks, spreadsheets, embedded analytics and AI systems. GraphQL and JDBC APIs and a Python SDK provide ways to query metrics and dimensions; Claude and ChatGPT can connect to governed metrics through the MCP server. Documented warehouse platforms include Snowflake, BigQuery, Databricks and Redshift. Defining and querying metrics requires a dbt Starter or Enterprise-tier account, and single-tenant accounts need account-representative setup and enablement. Starter includes 5,000 queried metrics per month; Enterprise and Enterprise+ each include 20,000. Starter costs $100 a month per user. The free Developer plan does not list the Semantic Layer.

Visit getdbt.com

Miller

Miller has no write-up on Specifiction yet; its figures are above.

Visit miller.readthedocs.io