Testing
Typesense is gaining ground as a fast, developer-friendly alternative to Algolia and Elasticsearch. Testing Typesense integrations well means covering three layers: the SDK client calls, the collection schema operations, and the search result assertions. This guide walks through all three. Typesense Testing Strategies There are two main approaches to
Testing
Elasticsearch query testing is notoriously difficult. The query DSL is complex, aggregations are stateful, and testing against a live cluster introduces flakiness. This guide covers testing strategies for Elasticsearch queries — from unit-level mock tests for query construction to Testcontainers integration tests that run against a real Elasticsearch node. The
Testing
Meilisearch has become a popular choice for teams that want fast, typo-tolerant search without the operational overhead of Elasticsearch. Its simple API makes it easy to integrate, but that same simplicity can give false confidence. Bugs in your indexing logic, filter syntax, or facet configuration don't announce
Testing
Algolia InstantSearch powers search experiences for thousands of production apps, but testing it reliably is harder than it looks. The library manages complex state — queries, filters, pagination, refinements — and testing against the live Algolia API in CI introduces latency, cost, and flakiness. This guide shows you how to test InstantSearch
Testing
OpenSearch — the open-source fork of Elasticsearch maintained by AWS — powers search for many production systems, particularly in AWS-native architectures. Testing OpenSearch presents similar challenges to Elasticsearch but with some important differences: the client SDK, the plugin ecosystem, and the AWS authentication layer all need specific testing strategies. This