Why Semantic Layers Matter (and how to build one with DuckDB)

The Role and Definition of a Semantic Layer

The discussion frequently returns to what a semantic layer actually is and what its purpose serves. Most agree it goes beyond a simple SQL VIEW, aiming to provide a shared understanding and consistent application of business logic and metrics.

• "A SQL VIEW is just a saved query, where a semantic layer defines the shared meaning of the data, and helps enforce consistent metrics, joins, and logic across tools." - CharlesW
• "Semantic Layer is about decomposing views into dimensions and aggregates, then letting downstream apps/users compose their own views on top without having to redefine/re-calculate business level metrics. This makes data analyis more flexible than sql views which are hardcoded on particular groupings." - aszen
• "a semantic layer helps express queries and their results in terms the end-consumers will care about / prefer to reason in, instead of whatever extremely correct and efficient atrocities the database nerds came up with." - btbuildem
• "More technically, it brings modularity and reusability to SQL. Things like joins, aggregate functions, and dimensional expressions are encapsulated as new fields/objects. Typically this logic is rendered at query time rather than pre-computed and materialized. The advantage of that is more flexible iteration and composability. In essence they are highly glorified SQL templating engines." - anon84873628
• aszen also mentioned, "Nothing to do with linear, meaningful projections on embedding spaces, and everything to do with efficient maintenance of legacy data reporting systems." - kovezd

Challenges and Adoption of Semantic Layers

A significant theme is the difficulty in adopting semantic layers within existing data workflows. The pressure to deliver immediate results often overrides the investment required for building reusable, semantic logic, leading to a proliferation of inconsistent and duplicated code.

• "Pivoting a decent sized BI shop toward using one instead of splashing the same SQL all over the place is tough. It's one of those: 'the analyst could have been building important report for director and you want them to create re-usable logic??? we'll do that later, get report done now. Just copy/paste that SQL over here'" - sschnei8
• "This is how you end up with the the 1000 model, 'the numbers don't match up', hot mess situations that gain momentum and are hard to slow down." - sschnei8
• "The problem is that often these quick or maybe not reusable are written in such a haste that there's no breadcrumbs left to do the right thing whenever you are done getting that urgent thing out (most likely never because 'everything is urgent' :(" - dietr1ch
• "Exactly. 'Everything is urgent' is the great burden of our time lol" - sschnei8
• "The semantic layer is like a capital investment that pays off over time. So it can be hard to justify the initial investment if people don't grok the payoff." - anon84873628
• The sentiment that "everything is urgent" is a recurring pain point in data engineering and analytics.

The Benefits of Semantic Layers: Reusability and Consistency

Despite the adoption challenges, many users highlight the long-term benefits of semantic layers, primarily centered around reusability, consistency, and making data more accessible and understandable for end-consumers.

• "The only way to build reports was from the semantic layer which was easy to use and built into the BI." - mritchie712
• "Semantic layers help expose a more user-friendly view of the data, so it is easier to ask business questions and get accurate results." - anon84873628
• "it's purely meant to run SQL transformations in DuckDB in a reliable way with data lineage." - mritchie712

Underlying Technologies and Implementation Preferences

There's a discussion about the best way to implement semantic layers, with opinions split on language choices and the need for robust tooling.

• "I think Common Logic ( https://en.m.wikipedia.org/wiki/Common_Logic - ISO/IEC 24707:2007) would be a good addition to any effort trying to add a semantic layer to any database." - whitten
• "I like the idea of a Semantic Layer but don't think defining it in yaml is the right way to go about it. Semantic Layer needs proper language and tooling support which Malloy provides." - aszen
• "Anything but a markup language / JSON." - kermatt
• "we built a transformation library[0] (think a simpler, more performant dbt) for duckdb and I'd really like to create a semantic layer as an extension for it at some point." - mritchie712
• "Limititing support to only duckdb would make some really useful features trivial to implement. e.g. duckdb has a json_serialize_sql function that would handle a lot of the tedious parts of building a semantic layer." - mritchie712
• "my key takeaway building this is that we need better expression systems and Ibis is a great foundation to build yours..maybe you want to build a language for some other domain etc." - mousematrix

Analogy to Other Data/Software Concepts

Users draw parallels to other concepts to help define and understand semantic layers, including ORMs and abstraction layers.

• "is a 'semantic layer' nothing more than a fancy name for a SQL VIEW in a NoSQL?" - cryptonector (This is met with a "No, it's more than that." from aszen)
• "hey all, another perspective that I have been thinking about is if semantic layers are like ORM for but BI dashboards. Actually, they I think its more than BI dashboards since a similar idea applies to Features. Features in ML land are nothing but a Measure + Entity metadata + TTL." - mousematrix
• "I think it's great that there are ARD formats and you can access bytes via low level s3 like protocol. This enables interesting tools like DuckDB which can abstract away some stuff, and be fastish and 'serverless'. However, clearly there is also some kind of marketing hype train and jargon built around it, and it seems like a concerted movement to displace some other 'boring' and 'uncool' products and technologies." - Demiurge (This comment raises a concern about potential jargon and hype, while still acknowledging the value of open formats.)