# Efficient COUNT, SUM, MAX with the Aggregate Component

DevFeed: [Efficient COUNT, SUM, MAX with the Aggregate Component](<https://devfeed.tech/articles/efficient-count-sum-max-with-the-aggregate-component-81343.md>)

Original publisher: [Read original article](<https://stack.convex.dev/efficient-count-sum-max-with-the-aggregate-component>)

Author: Stack

Published: 2025-08-16T05:46:00Z

Content type: tutorial

Language: en

Sources: [Stack](<https://devfeed.tech/sources/stack.md>)

Topics: [database-optimization](<https://devfeed.tech/topics/database-optimization.md>), [database-consistency](<https://devfeed.tech/topics/database-consistency.md>), [cosine similarity search](<https://devfeed.tech/topics/cosine-similarity-search.md>)

Tags: [aggregate](<https://devfeed.tech/tags/aggregate.md>), [aggregates](<https://devfeed.tech/tags/aggregates.md>), [b-tree](<https://devfeed.tech/tags/b-tree.md>), [database](<https://devfeed.tech/tags/database.md>), [migrations](<https://devfeed.tech/tags/migrations.md>), [triggers](<https://devfeed.tech/tags/triggers.md>)

## AI overview

This tutorial demonstrates using Convex's Aggregate Component for efficient pagination, ranking, per-user statistics, random selection, and latency statistics. It covers keeping aggregates synchronized with database changes using triggers and custom functions, backfilling existing data with migrations, and the risks of edits made through the dashboard that bypass triggers.

## Source excerpt

Convex omits built-in aggregates because full-table scans don't scale; the video shows how @convex-dev/aggregate (B-Tree powered) enables fast pagination, ranking, per-user stats, and randomization with fully reactive queries. It also covers keeping aggregates in sync via triggers/custom functions, backfilling with migrations, and the trade-offs that hint at possible platform-level support.