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Elasticsearch vs Algolia: Complete Comparison Guide

Compare Elasticsearch and Algolia on search functionality, management, cost, and integration. Discover which search solution is the best fit for your application.

Elasticsearch

An open-source distributed search and analytics engine built on Apache Lucene. Elasticsearch provides powerful full-text search, structured queries, analytics, and log aggregation. It can be self-hosted or used via Elastic Cloud, and is deployed worldwide for search applications, observability, and security analytics.

Algolia

A fully managed search-as-a-service solution optimized for speed and relevance. Algolia delivers search results within milliseconds with built-in typo tolerance, faceted search, and personalization. The platform offers ready-made UI components and is designed for a frontend-first search experience.

Comparison table

FeatureElasticsearchAlgolia
HostingSelf-hosted or Elastic Cloud — full control possibleFully managed SaaS — no infrastructure management needed
Search speedFast, but requires tuning for optimal search latencyUltra-fast search results within 1-20 ms out-of-the-box
Typo toleranceConfigurable via fuzzy queries — manual tuning neededBuilt-in typo tolerance and linguistic matching
AnalyticsPowerful analytics and aggregations for log and event dataSearch analytics and click-through tracking for search optimization
ComplexitySteep learning curve — requires expertise for cluster managementLow — quick integration via API and ready-made UI components
CostOpen-source free; Elastic Cloud from ~$95/monthFree up to 10,000 requests/month; then based on records and searches

Verdict

Elasticsearch and Algolia serve overlapping but different markets. Elasticsearch is a versatile platform combining search, analytics, and observability with full control via self-hosting. However, it requires expertise for optimal configuration. Algolia is optimized for one thing: a fast, relevant search experience with minimal setup. The choice depends on your needs: a broadly deployable search and analytics engine (Elasticsearch) or a polished, instant search experience without operational overhead (Algolia).

Our recommendation

At MG Software, we choose the best search solution per project. For clients wanting a fast search experience on their website or app without complex infrastructure, we implement Algolia for its speed and easy integration. For projects that need analytics, logging, or complex aggregations alongside search, we deploy Elasticsearch. As a lightweight alternative, we also increasingly recommend Meilisearch or the built-in full-text search of PostgreSQL via Supabase.

Further reading

What is SQL?Supabase vs Firebase comparisonPrisma vs Drizzle comparison

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Frequently asked questions

For frontend search experience, Algolia is typically faster out-of-the-box, with results within 1-20 ms. Elasticsearch can achieve comparable speeds but requires careful tuning of indices, mappings, and queries. Algolia is optimized for instant search response, while Elasticsearch is more broadly applicable.
Algolia offers a free tier up to 10,000 searches per month. For an average e-commerce store with 100,000 searches per month, costs are around $50-150/month, depending on the number of records and additional features like analytics and A/B testing.
Yes, some organizations use Elasticsearch for backend analytics and logging, and Algolia for the frontend search experience. This combines the analytical power of Elasticsearch with the speed and simplicity of Algolia, but increases the complexity and cost of the architecture.

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