Top all-time · #2067
cube.dev
Company blog · cube.dev/blog · on HN as pavel_tiunovdataprogramming
cube.dev is the company blog at cube.dev, writing about data and programming. Since 2019, 37 different Hacker News readers have linked it 73 times, most often “Cube.js – Open-Source Analytics Framework”. No feed was found, so read it on the site itself.
Too few sampled comments (29) to say how often HN recommends it.?
Why HN links it
HN readers cite Cube's blog for explanations of semantic layers, headless BI, and the DeWitt clause on database benchmarking. These posts are usually given as background sources in discussions of BI and SQL tooling.
Summarised by Claude from a sample of 29 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.
Cube is the agentic analytics platform, built on a semantic layer — AI-native business intelligence and embedded analytics with answers your team and your customers can trust.
Most-linked posts?
- Cube.js – Open-Source Analytics Framework10 people · 14 mentions · first linked 2019-04-03
- DeWitt Clause, or can you benchmark %database% and get away with it5 people · 6 mentions · first linked 2022-06-02
- /3 people · 3 mentions · first linked 2021-12-01
- AI-powered conversational interface for the semantic layer2 people · 2 mentions · first linked 2023-04-18
- First production-grade use case for DuckDB and MotherDuck?2 people · 2 mentions · first linked 2023-08-22
- The Semantic Layer is key for streamlining dev of high-quality AI apps2 people · 2 mentions · first linked 2023-06-22
What Hacker News says?
We use https://cube.dev/ as intermediate layer between data warehouse database and Superset (and other "terminal" apps for BI like report generators). You define your schema (metrics, dimensions, joins, calculated metrics etc) in cube and then access them by any tool that can connect to SQL db
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on “Apache Superset”Submitted DeWitt Clause, or can you benchmark %database% and get away with it as a story · 109 points
HN discussionthe short answer: use a semantic layer. It's the cleanest way to give the right context and the best place to pull a human in the loop. A human can validate and create all important metrics (e.g. what does "monthly active users" really mean) then an LLM can use that metric definition whenever asked for MAU. With a semantic layer, you get the added benefit of writing queries in JSON instead of raw SQL. LLM's are much…
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on “Getting AI to write good SQL”Submitted Cube.js – Open-Source Analytics Framework as a story · 20 points
HN discussionWas about to say the same. Last year I went through a huge industry comparison exercise for my former company. Spent 6 months evaluating BI tooling. Every option out there is ridiculously expensive. Looker quoted us at $1M/year, though they were using the sticker shock strategy to get us around a $200K/year price point. I came away with the impression that BI is simply not accessible outside of enterprise level orgs…
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on “Open source Business intelligence platform made with Python”Submitted DeWitt Clause, or Can You Benchmark %Database% and Get Away with It as a story · 7 points
HN discussionyes, that shouldn't be a problem. with that many tables, you might want to use Views: https://cube.dev/docs/reference/data-model/view
Comment linking /docs/reference/data-model/view
on “Building AI agents to query your databases”Submitted AI-powered conversational interface for the semantic layer as a story · 3 points
HN discussionUsing a semantic layer is the cleanest way to have a human in the loop. A human can validate and create all important metrics (e.g. what does "monthly active users" really mean) then an LLM can use that metric definition whenever asked for MAU. With a semantic layer, you get the added benefit of writing queries in JSON instead of raw SQL. LLM's are much more consistent at writing a small JSON vs. hundreds of lines o…
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on “Building AI agents to query your databases”Submitted Open Source Looker Alternative with Cube and Superset as a story · 3 points
HN discussionI'm not too familiar with https://cube.dev/ - but my initial impression is they are focused more on providing APIs backed by SQL. They have a SQL API that emulates the PostgreSQL wire protocol, whereas Spice implements Arrow and Flight SQL natively. Their pre-aggregations are a similar concept to Spice's data accelerators. It also looks like they have their own query language, whereas Spice is native SQL as well.
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on “Show HN: Spice.ai – materialize, accelerate, and query SQL data from any source”Submitted Time Series Data Analytics with QuestDB and Cube as a story · 3 points
HN discussionFrom the article: > There's a lot of information out there, including from myself about the history and rise [2022], comparing it to an MVC-like approach, or explaining its capabilities. That's why in this article I focus on the why and showcase how to use it in a practical example in the next chapter. [1] https://www.ssp.sh/blog/rise-of-semantic-layer-metrics/ [2] https://cube.dev/blog/exploring-the-semantic-layer-…
Comment linking /blog/universal-semantic-layer-capabilities-integrations-and-enterprise-benefits
on “Why Semantic Layers Matter (and how to build one with DuckDB)”Submitted Cube: Headless BI as a story · 3 points
HN discussionThere is a small list of vendors that do not forbid to run benchmarks with their systems. https://cube.dev/blog/dewitt-clause-or-can-you-benchmark-a-d... That is why there is a small subset of vendors that are being 'attacked' by this comparisons.
Comment linking /blog/dewitt-clause-or-can-you-benchmark-a-database
on “No, QuestDB is not Faster than ClickHouse”Submitted React Visualization Libraries in 2019 as a story · 3 points
HN discussionI've added BigQuery and run the benchmark and get the results... but due to their ToS , the benchmark results cannot be published. See https://cube.dev/blog/dewitt-clause-or-can-you-benchmark-a-d... The benchmark instructions for BigQuery are here: https://github.com/ClickHouse/ClickBench/tree/main/bigquery If you follow them, just add the .json with the results and regenerate the HTML with the generate-results.sh s…
Comment linking /blog/dewitt-clause-or-can-you-benchmark-a-database
on “Show HN: A benchmark for analytical databases (Snowflake, Druid, Redshift)”Submitted Why Agentic AI Needs a Semantic Core as a story · 2 points
HN discussionNope, those are the primary components of a semantic layer. Most other semantic layer products have three main components: input data sources -- typically SQL queries or table names, configuration -- the semantic layer describing all the things you mention above, relative to the input data sources, and the access layer -- usually a non-SQL API that consumers must use to consume data that has been modeled by the sema…
Comment linking /docs/query-format
on “A sequel to SQL? An intro to Malloy”Submitted Query Latency in the Age of AI Agents as a story · 2 points
HN discussionIt only works if you are just running queries in console. Any serious work with sql requires all sorts of weird stuff built around it like dbt, cubejs[1]. 1. https://cube.dev/docs/
Comment linking /docs/
on “A sequel to SQL? An intro to Malloy”Submitted CubeJS – A Universal OSS Semantic Layer (Maturity?) as a story · 2 points
HN discussionIn essence, you may want Hasura/GraphQL if you have no idea how the end-users' query format will look, whereas Cube is well-suited for providing performant results for somewhat predictable sets of queries. Disclaimer: I work on Cube. My colleague Igor explains it better: Hasura is for CRUD with reasonable performance, Cube is for fetching analytical (quantitative) data with sub-second latency and high concurrency. H…
Comment linking /blog/category/user-stories/
on “Cube.js – Open-Source Analytics API for Building Data Apps”Submitted MVC Pattern Applied to Data: Rethinking the Semantic Layer as a story · 2 points
HN discussionLong time ago, it was possible to built Cube into a Node.js app. However, the team decided to deprecate it: https://github.com/cube-js/cube.js/blob/master/DEPRECATION.m... The motivation is diverse but one of the reasons is that a Cube app should be scaled differently from a client-facing app. Noone probably wants their app to hang when Cube serves a ton of requests or refreshes cached data (and vice versa). That’s…
Comment linking /cloud/
on “Cube.js – Open-Source Analytics API for Building Data Apps”Submitted Direct Connect to Excel from Databricks or Snowflake Through Cube as a story · 2 points
HN discussionHey! Igor from the Cube team here. Coincidentally, in a few days, we’re having a workshop on multitenancy where we’ll cover dynamic schemas: https://cube.dev/events/multitenancy . We’ll show how to customize schemas using pure JavaScript.
Comment linking /events/multitenancy
on “Cube.js – Open-Source Analytics API for Building Data Apps”Submitted Sub Second Query Performance as a story · 2 points
HN discussionI should have clarified. There's a large number of apps that are: 1. taking info strictly from SQL (e.g. information_schema, query history) 2. taking a user input / question 3. writing SQL to answer that question An app like this is what I call "text-to-sql". Totally agree a better system would pull in additional documentation (which is what we're doing), but I'd no longer consider it "text-to-sql". In our case, we'…
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on “MQL – Client and server to query your db in natural language”Submitted Cube integrates with LangChain, so you don't need to write SQL anymore as a story · 2 points
HN discussion
