Instant SQL for results as you type in DuckDB UI

Original Article ↗ Hacker News Discussion ↗

Overall Reception

  • Many commenters are enthusiastic about Instant SQL, calling it “awesome,” “such a good idea,” and especially valuable for debugging complex transformations and regexes.
  • Some users say it would have saved significant time in past analytics/debugging work and makes DuckDB even more attractive compared to pandas/SQLite-era workflows.
  • A few find the concept “bizarre” at first, then accept it as powerful given DuckDB’s architecture and caching.

Execution Behavior & Safety

  • Multiple jokes and worries about DELETE/DROP/destructive queries running automatically.
  • DuckDB/MotherDuck engineers clarify: Instant SQL only auto-runs SELECT (read-only) queries; writes/deletes and metadata changes are not executed.
  • One suggestion: run everything in a non-committed transaction; but core reassurance is that previews are read-only.

UX Feedback, Controls & Bugs

  • Users request tuning when previews run to avoid distracting red errors on every keystroke (e.g., trigger on spaces/commas, semicolons, paste/autocomplete).
  • Some report CTE selection errors (wrong segment selected, frequent failures); maintainers ask for repro queries.
  • One user initially struggles to install the UI extension; newer DuckDB version resolves it.

CTE/Subquery Inspection & AST Features

  • CTE and subquery preview is widely praised as “amazing”; people note they currently emulate this manually (running partial queries, stepwise SQL in Python).
  • The implementation relies on json_serialize_sql plus cursor-to-AST mapping; this unlocks future debugging/introspection features.
  • There’s interest in editing JSON AST back into SQL and in using AST-aware tooling for performance tuning.

Syntax Debates (FROM-first, Pipes, Alternatives)

  • FROM-first SQL supported by DuckDB triggers debate:
    • Supporters say it improves autocomplete and aligns with LINQ/pipe-style thinking.
    • Critics argue it weakens established conventions and that smart autocomplete works fine with standard order.
  • Several argue DuckDB “misses” pipe syntax like Kusto/BigQuery; pipes are seen as more intuitive, more LLM-friendly, and better for left-to-right thinking.
  • Alternatives mentioned: PRQL, Malloy, BigQuery pipes, DuckDB PRQL/psql extensions, q-SQL; reactions range from interest to “nightmarish”/“horrendous syntax.”

Offline, Open Source & Notebook Concerns

  • Users in regulated environments want a fully offline UI and ask about open-sourcing; maintainers say both are planned but not yet done.
  • Current UI downloads assets at runtime; an offline mode is on the roadmap.
  • DuckDB notebooks are liked for exploration, but lack of easy export/versioning/sharing (e.g., via Git) is seen as limiting; users point to third-party notebook tools as workarounds.

Ecosystem, Performance & Commercialization

  • Users ask how Instant SQL behaves on large joins and complex queries; no concrete performance data is shared, but caching is implied as key.
  • Several tools/projects are referenced as complementary (type-safe SQL, PRQL IDEs, notebooks around DuckDB/Polars).
  • One commenter feels uneasy about a commercial company closely embracing a beloved OSS project, though specifics are not elaborated.