BEAVER: Enterprise benchmark for LLM Text-to-SQL from private data warehouses
BEAVER is a large-scale enterprise text-to-SQL dataset containing 9128 queries across 19 diverse domains. The dataset is composed of queries and databases collected from private organizations, with 7978 queries publicly released and the remaining portion held out as a private test set. The dataset provides annotations for five subtasks to facilitate fine-grained evaluation and analysis.
- ▪BEAVER contains 9128 queries spanning 812 tables across 19 diverse domains.
- ▪The dataset includes 7978 publicly released queries and a private test set.
- ▪The dataset provides annotations for five subtasks: multi-table retrieval, join key detection, column mapping, domain knowledge extraction, and query decomposition.
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Story provenance
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Github |
| Canonical URL | https://beaverbench.github.io/ |
| Publication time | Mon, 15 Jun 2026 01:20:49 +0000 |
| Retrieval time | 2026-06-15T01:32:35.019Z |
| Last seen | 2026-06-15T01:32:35.019Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | tE-62AoOhIy8 |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
BEAVER is a large-scale enterprise text-to-SQL dataset containing 9128 queries spanning 812 tables across 19 diverse domains. Of these, 7978 queries are publicly released, while the remaining portion is held out as a private test set. Queries and databases were collected from private organizations. To facilitate fine-grained evaluation and analysis, we provide annotations for five subtasks: multi-table retrieval, join key detection, column mapping, domain knowledge extraction, and query decomposition three categories of queries: complex queries without domain knowledge, domain-specific queries with minimal complexity, and domain-specific complex queries
Excerpt limited to ~120 words for fair-use compliance. The full article is at Github.
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