Approximate, streaming SQL engine
Project description
📊 StatQL
StatQL is a desktop‑first SQL engine that streams fast, approximate answers from your data sources—without spinning up a server.
Initial release ships with connectors for PostgreSQL, Redis (α quality) and the local Filesystem. More catalogs—cloud object storage, OLAP warehouses, REST APIs—are on the roadmap.
pip install statql
python -m statql # launches the Streamlit UI in your browser
Usage examples
StatQL emits a fresh result table every 0.5 – 1 s. Each numeric cell is formatted as
value ± error, where error is the absolute 95 % confidence‑interval half‑width. As more of the population is sampled, the estimates tighten.
1️⃣ Row count per order status (single table)
SELECT l_linestatus, COUNT() AS rows
FROM pg.local.tpch.public.lineitem
GROUP BY l_linestatus;
| l_linestatus | rows |
|---|---|
| F | 3 172 481 ± 46 892.7 |
| O | 3 181 633 ± 46 744.2 |
2️⃣ Total PNG footprint in /data/images (filesystem)
SELECT divide(SUM(size), 1_073_741_824) AS gib
FROM fs.media_fs.entries
WHERE get_file_ext(path) = 'png';
| gib |
|---|
| 118.6 ± 5.3 |
3️⃣ Row counts across all databases in a cluster (wildcards)
SELECT @db, COUNT() AS rows
FROM pg.us-cluster-4.?.public.lineitem
GROUP BY @db
ORDER BY rows DESC;
| @db | rows |
|---|---|
| sales | 12 945 002 ± 99 811.4 |
| hr | 6 088 551 ± 74 225.9 |
| … | … |
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