Meilisearch: Self-Hosted Search Engine

Meilisearch is a lightning-fast, typo-tolerant search engine designed to deliver relevant results in under 50 milliseconds. With over 55,000 GitHub stars, it has become one of the most popular open-source alternatives to Algolia and Elasticsearch for developers who need a simple, powerful search API. Meilisearch handles filtering, faceting, sorting, and multi-language support right out of the box.

Self-hosting Meilisearch means your search index and user query data stay entirely on your infrastructure — no API call limits, no per-search pricing, and no data leaving your network.

Key Features

• Sub-50ms search responses with instant typo-tolerant matching
• RESTful API with SDKs for JavaScript, Python, Ruby, Go, PHP, and more
• Faceted search and filtering for building refined product or content discovery
• Multi-index support for searching across different datasets simultaneously
• Customizable ranking rules to control how results are scored and ordered
• Built-in synonyms and stop words configuration for natural language search
• Document management with partial updates and batch indexing
• Tenant tokens for multi-tenant search with per-user data isolation

Why Self-Host Meilisearch?

Zero per-search costs. Managed search services like Algolia charge per search request and per record, which adds up fast at scale. Self-hosted Meilisearch runs on a fixed-cost VPS — whether your users run 100 or 100,000 searches per day, the cost stays the same.

Complete data control. Search indexes often contain sensitive product data, user content, or internal documents. Self-hosting ensures your entire search corpus and query logs remain on your own server, meeting compliance requirements without extra effort.

No rate limits or quotas. Cloud search providers throttle indexing speed and limit document counts on lower tiers. A self-hosted instance gives you unlimited indexing throughput and index sizes bound only by your server's resources.

Low-latency integration. When Meilisearch runs on the same network as your application, search queries avoid the round-trip to an external API. This shaves precious milliseconds off response times, which directly impacts user experience.

System Requirements

Resource	Minimum	Recommended
CPU	1 vCPU	2+ vCPUs
RAM	1 GB	4 GB
Storage	10 GB SSD	40 GB SSD
OS	Ubuntu 22.04+	Ubuntu 24.04

Meilisearch loads indexes into memory for fast retrieval, so RAM requirements scale with the size of your dataset. For indexes under 1 million documents, 2 GB RAM is typically sufficient. Larger datasets benefit from additional memory and NVMe storage.

Getting Started

The fastest way to deploy Meilisearch on your VPS is with Docker Compose through Dokploy. Our step-by-step deployment guide walks you through the full setup, including persistent storage, environment configuration, and SSL.

Deploy Meilisearch with Dokploy →

Alternatives

• Elasticsearch — Distributed search and analytics engine built for large-scale enterprise workloads
• Typesense — Typo-tolerant search engine with an emphasis on developer experience and simplicity
• Manticore Search — High-performance search engine forked from Sphinx with SQL-like query syntax
• Zinc — Lightweight Elasticsearch alternative written in Go for log search and application search

FAQ

How does Meilisearch compare to Elasticsearch? Meilisearch is designed for instant, user-facing search with minimal configuration. Elasticsearch is more powerful for complex analytics and log aggregation but requires significant operational overhead. For product search, site search, or content discovery, Meilisearch is faster to set up and easier to maintain.

Can Meilisearch handle large datasets? Yes. Meilisearch can index millions of documents effectively. Performance depends on available RAM since indexes are memory-mapped. For datasets exceeding a few million records, provision your VPS with enough memory to hold the index comfortably.

Is Meilisearch production-ready? Meilisearch reached v1.0 stability and offers a reliable API with backward-compatible updates. Many companies use it in production for customer-facing search. The project follows semantic versioning, so breaking changes are clearly communicated.

Does Meilisearch support authentication? Yes. Meilisearch uses API keys with configurable permissions. You can create read-only search keys for frontend use and admin keys for indexing. Tenant tokens allow multi-tenant setups where each user only sees their own data in search results.

---

App data sourced from selfh.st open-source directory.