data-research

Build scalable SQL aggregations by moving data summarization directly into SQL queries against Postgres tables, ensuring dashboards render fast without loading raw data into memory. This approach enforces DB-only reads and bounded results to maintain dashboard performance.

Dashboards run out of memory when loading raw data for client-side aggregation. Moving these aggregations into SQL against Postgres tables ensures the database handles summarization, bounding results and preventing memory exhaustion during render.

Migrate JavaScript aggregations to SQL by applying provided recipes that translate JS logic into Postgres queries. Validate the migration using parity tests to ensure the SQL output matches the original JS results before fully switching the render path.

Yes, you can compute histogram analytics directly in Postgres. Ask the agent to generate a SQL aggregation that computes a bounded histogram of fill sizes for the target wallet, enforcing single-source truth and DB-only reads on the render path.

Yes, the approach enforces traceable explain plans for SQL queries. It applies core principles ensuring query transparency and performance validation when summarizing large datasets for analytics and dashboard slices.

Avoid SQL-based aggregations if your dataset is small enough for in-memory processing or if your data store lacks advanced SQL support. This approach targets summarizing millions of rows in Postgres where memory constraints impact dashboard rendering.