Case Study: Nextdoor achieves scalable, multi-region group querying and reduced Postgres contention with FaunaDB

Scaling community interactions with FaunaDB

Nextdoor, a large social network for neighborhood conversations, faced growing performance and operational challenges: complex, IO‑intensive queries to compile user lists for broadcast alerts were overloading their PostgreSQL deployment. They needed a cloud-native, horizontally scalable, multi-region database with strong consistency and support for complex relational and graph‑like queries. To meet these requirements, Nextdoor turned to Fauna and its FaunaDB offering.

Fauna implemented FaunaDB with robust multi‑region replication, strong consistency, ACID transactions and a multi‑model query language that supports nested joins and set intersections. As a result, Nextdoor isolated the groups workload so group queries no longer contend with other application traffic, gained global availability and scalability, and can now programmatically compose complex queries and add new workloads via FaunaDB’s multi‑tenancy—improving performance, availability and developer productivity.

Nextdoor

Prakash Janakiraman

Co-Founder and Chief Architect