u/mr_gnusi

A VSCode-inspired, open-source UI for Postgres

A VSCode-inspired, open-source UI for Postgres

We’ve been trying to bring some VSCode experience (command palette, split panes, etc.) to Postgres. We thought it might be useful for anyone else looking for a minimalistic, keyboard-first setup.

Highlights:

  • Navigation: Command palette (Cmd+K) for keyboard-first navigation.
  • Layout: Split and movable tabs for managing multiple queries.
  • Workspace: State is shared across connections and databases.
  • Autocomplete: Context-aware suggestions based on your schema.
  • Visuals: Built-in graphing directly from query results.
  • History: Searchable query history that feeds into autocomplete.

It’s open-source and we’re looking for feedback: what's good or bad in your opinion?

GitHub: https://github.com/serenedb/serenedb/tree/main/serene-ui

youtube.com
u/mr_gnusi — 4 days ago
▲ 24 r/SQL+1 crossposts

Zero-ETL search (BM25, vector) over remote Parquet/Iceberg in Postgres SQL

If you want to run BM25 ranking or vector search on data lakes (over remote data), you usually have to move or copy that data into a search engine or a dedicated database. 

I've prepared a short demo on how you can search over remote data directly from SQL.

For context:

I'm working on a Postgres-compatible search-OLAP database called SereneDB and we've just recently pushed this "Zero-ETL" feature to our repo and are looking for feedback! 

Specifically, I'm curious:

  1. Do you find this Zero-ETL thing useful?
  2. Does the SQL interface feel natural for BM25/ranking?
github.com
u/mr_gnusi — 4 days ago
▲ 110 r/SQL+1 crossposts

We’ve been trying to bring some VSCode experience (command palette, split panes, etc.) to Postgres. We thought it might be useful for anyone else looking for a minimalistic, keyboard-first setup.

Highlights:

  • Navigation: Command palette (Cmd+K) for keyboard-first navigation.
  • Layout: Split and movable tabs for managing multiple queries.
  • Workspace: State is shared across connections and databases.
  • Autocomplete: Context-aware suggestions based on your schema.
  • Visuals: Built-in graphing directly from query results.
  • History: Searchable query history that feeds into autocomplete.

It’s open-source and we’re looking for feedback: what's good or bad in your opinion?

GitHub: https://github.com/serenedb/serenedb/tree/main/serene-ui

u/mr_gnusi — 15 days ago

Adaptive compression is critically important for analytical workloads as it reduces storage costs and can dramatically speedup query execution. Great reads on this: DuckDB lightweight compression, BtrBlocks and FastLanes.

Inverted indexes deal with millions of sorted integers and could benefit from the same ideas, but posting lists have their own specifics: values are monotonically increasing integers, blocks are much smaller compared to columnar storage and the access pattern is typically different.

The article is a deep dive into how we implemented per-block adaptive compression for our open-source inverted indexing engine IResearch, what problems we ran into and how we solved them.

GitHub: https://github.com/serenedb/serenedb

u/mr_gnusi — 22 days ago