# Implement a correctness-safe Bloom filter lookup with Amazon ElastiCache for Valkey and Amazon Aurora PostgreSQL

DevFeed: [Implement a correctness-safe Bloom filter lookup with Amazon ElastiCache for Valkey and Amazon Aurora PostgreSQL](<https://devfeed.tech/articles/implement-a-correctness-safe-bloom-filter-lookup-with-amazon-elasticache-for-valkey-and-amazon-aurora-postgresql-42098.md>)

Original publisher: [Read original article](<https://aws.amazon.com/blogs/database/implement-a-correctness-safe-bloom-filter-lookup-with-amazon-elasticache-for-valkey-and-amazon-aurora-postgresql/>)

Author: Chintan Agrawal

Published: 2026-09-17T16:01:43Z

Content type: tutorial

Language: en

Sources: [AWS Database Blog](<https://devfeed.tech/sources/aws-database-blog.md>)

Topics: [bloom-filter](<https://devfeed.tech/topics/bloom-filter.md>), [valkey](<https://devfeed.tech/topics/valkey.md>), [Amazon Aurora](<https://devfeed.tech/topics/amazon-aurora.md>), [Cache](<https://devfeed.tech/topics/cache.md>), [PostgreSQL](<https://devfeed.tech/topics/postgresql.md>), [Caching](<https://devfeed.tech/topics/caching.md>), [consistency](<https://devfeed.tech/topics/consistency.md>), [Latency](<https://devfeed.tech/topics/latency.md>)

Tags: [advanced-300](<https://devfeed.tech/tags/advanced-300.md>), [amazon-aurora](<https://devfeed.tech/tags/amazon-aurora.md>), [amazon-elasticache](<https://devfeed.tech/tags/amazon-elasticache.md>), [architecture](<https://devfeed.tech/tags/architecture.md>), [bloom-filter](<https://devfeed.tech/tags/bloom-filter.md>), [cache](<https://devfeed.tech/tags/cache.md>), [consistency](<https://devfeed.tech/tags/consistency.md>), [latency](<https://devfeed.tech/tags/latency.md>), [performance](<https://devfeed.tech/tags/performance.md>), [postgresql](<https://devfeed.tech/tags/postgresql.md>), [postgresql-compatible](<https://devfeed.tech/tags/postgresql-compatible.md>), [technical-how-to](<https://devfeed.tech/tags/technical-how-to.md>), [valkey](<https://devfeed.tech/tags/valkey.md>)

## AI overview

This post explains a three-tier membership lookup that combines a Bloom filter in Amazon ElastiCache for Valkey, an exact-match cache, and Amazon Aurora PostgreSQL as the relational source of truth. The design provides fast negative checks and preserves correctness when false positives would affect business outcomes.

## Source excerpt

This post shows how to compose a Bloom filter with an exact-match cache and a relational source of truth into a three-tier, correctness-safe membership lookup using Amazon ElastiCache for Valkey and Amazon Aurora PostgreSQL, serving sub-millisecond decisions at peak throughput without false-positive risk.