EQQ is built to serve a business-user workload (10k-1M row results, dozens of concurrent users) rather than a data-science workload (billion-row scans). Within that envelope, it scales well. Here is how.

The result-size dial

Every query has a Max Rows setting. Below it, EQQ streams rows to the browser grid and offers inline export. Above it, EQQ auto-promotes the run to a background job: the grid closes, the user gets a notification, the result file lands in Background Jobs for download.

Excel 1,048,576 row ceiling

When exporting to .xlsx, EQQ detects the ceiling and splits across sheets automatically. CSV has no ceiling. JSON is streamed, so you can pipe it to any script without materializing in memory.

The result grid handles large datasets - rows stream in progressively and a banner warns when results exceed the on-screen page.
The result grid handles large datasets - rows stream in progressively and a banner warns when results exceed the on-screen page.

Timeout strategy

  • Interactive timeout - short (30s default). Protects the UI from bad queries.
  • Background timeout - long (configurable). Lets legitimate long-runs finish.
  • Clone timeout - separate setting in Web.config for cross-database clones.

Concurrency

The bottleneck at scale is almost always the source database, not EQQ. Add indexes on the columns your parameters filter by; prefer Views over raw table projections; cache slow-changing reference data inside the database itself.

Monitoring

Every execution is audited with elapsed time. Query the audit table for the 90th percentile and you will find your slow queries fast - often 2-3 queries are responsible for 80% of the wait time.

Want to see it live? Book a 30-minute demo - we connect EQQ to your database and build a query with you. Book a Demo →