---
title: Bloom Filters and HyperLogLog in Production on ElastiCache Redis
description: Bloom filters shave 90% of negative lookups; HyperLogLog estimates cardinality without storing every user ID. Redis modules on ElastiCache for abuse detection and feed deduplication.
url: https://www.factualminds.com/blog/bloom-filters-hyperloglog-production-elasticache/
datePublished: 2026-06-12T00:00:00.000Z
dateModified: 2026-06-12T00:00:00.000Z
author: Palaniappan P
category: Cloud Architecture
tags: engineering-guide, redis, elasticache, performance, aws
---

# Bloom Filters and HyperLogLog in Production on ElastiCache Redis

> Bloom filters shave 90% of negative lookups; HyperLogLog estimates cardinality without storing every user ID. Redis modules on ElastiCache for abuse detection and feed deduplication.

**ElastiCache Redis (June 2026)** supports **Bloom filters** (RedisBloom module where enabled) and **HyperLogLog** (`PFADD`/`PFCOUNT`) natively—cheap cardinality for “how many unique IPs today?” without Prometheus label explosion.

## Bloom filter

- **Use:** “Have we seen this dedup key?” with false positives OK
- **Avoid:** Need exact membership proof for billing

Configure expected items and false positive rate; size is fixed at creation.

## HyperLogLog

~12 KB per key for ~0.81% error on billions of uniques—perfect for **dashboard UV** metrics, not invoicing.

## AWS patterns

| Use case        | Structure                                       |
| --------------- | ----------------------------------------------- |
| API abuse       | Bloom per IP window in Redis                    |
| Unique visitors | HLL per day, export to CloudWatch custom metric |
| Feed dedup      | Bloom + DynamoDB for positives                  |

## What to do this week

1. Replace `SET` of all session IDs with HLL for daily active count dashboard.
2. Add Bloom pre-check before expensive Aurora query.
3. Monitor Redis memory—Bloom is cheaper than full SET until false positive rate hurts UX.

## What this guide doesn't cover

General cache invalidation—part 2 of caching track.

---

*Source: https://www.factualminds.com/blog/bloom-filters-hyperloglog-production-elasticache/*