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Alex Spinov
Alex Spinov

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Typesense Has a Free Open-Source Search Engine Built for Speed

#opensource #search #webdev #javascript

Typesense is a free, open-source search engine that's optimized for instant search-as-you-type experiences. Built in C++, it delivers sub-millisecond search results.

What Is Typesense?

Typesense is a typo-tolerant, blazing-fast search engine designed as an easier-to-use alternative to Elasticsearch and a free alternative to Algolia.

What makes it special:

  • Sub-millisecond search latency
  • Typo tolerance out of the box
  • Tunable ranking and relevance
  • Faceting and filtering
  • Geo search
  • Vector search (AI-powered semantic search)
  • Scoped API keys (multi-tenancy)
  • Single binary, no dependencies
  • High availability with built-in replication

Quick Start

Install 

# Docker
docker run -p 8108:8108 \
  -v /tmp/typesense-data:/data \
  typesense/typesense:27.1 \
  --data-dir /data \
  --api-key=your-api-key

# macOS
brew install typesense/tap/typesense-server
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Create a Collection 

curl "http://localhost:8108/collections" \
  -X POST \
  -H "X-TYPESENSE-API-KEY: your-api-key" \
  -d '{
    "name": "products",
    "fields": [
      {"name": "name", "type": "string"},
      {"name": "price", "type": "float"},
      {"name": "category", "type": "string", "facet": true},
      {"name": "rating", "type": "float"}
    ],
    "default_sorting_field": "rating"
  }'
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Add Documents 

curl "http://localhost:8108/collections/products/documents" \
  -X POST \
  -H "X-TYPESENSE-API-KEY: your-api-key" \
  -d '{"name": "Ergonomic Keyboard", "price": 89.99, "category": "Electronics", "rating": 4.8}'
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Search 

curl "http://localhost:8108/collections/products/documents/search?q=keybrd&query_by=name" \
  -H "X-TYPESENSE-API-KEY: your-api-key"
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Returns "Ergonomic Keyboard" despite the typo. In <1ms.

JavaScript SDK 

import Typesense from "typesense";

const client = new Typesense.Client({
  nodes: [{ host: "localhost", port: 8108, protocol: "http" }],
  apiKey: "your-api-key"
});

// Search
const results = await client.collections("products").documents().search({
  q: "keyboard",
  query_by: "name",
  filter_by: "price:<100",
  sort_by: "rating:desc",
  facet_by: "category"
});
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Vector Search (AI-Powered)

Typesense supports semantic search with vector embeddings:

// Create collection with vector field
await client.collections().create({
  name: "docs",
  fields: [
    { name: "title", type: "string" },
    { name: "content", type: "string" },
    { name: "embedding", type: "float[]", num_dim: 384 }
  ]
});

// Search by meaning, not just keywords
const results = await client.collections("docs").documents().search({
  q: "how to deploy containers",
  query_by: "embedding",
  prefix: false
});
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Typesense vs Alternatives

Feature Elasticsearch Algolia Typesense
Latency 10-100ms <10ms <1ms
Setup complexity High None (SaaS) Low
Typo tolerance Plugin Built-in Built-in
Vector search Plugin No Built-in
Self-host Yes No Yes
RAM usage 2GB+ N/A 256MB+
Free tier Self-host 10K req/mo Unlimited
License SSPL Proprietary GPL-3.0

InstantSearch UI

Typesense works with Algolia's InstantSearch.js UI components:

import instantsearch from "instantsearch.js";
import { searchBox, hits } from "instantsearch.js/es/widgets";
import TypesenseInstantSearchAdapter from "typesense-instantsearch-adapter";

const adapter = new TypesenseInstantSearchAdapter({
  server: { nodes: [{ host: "localhost", port: 8108, protocol: "http" }], apiKey: "search-key" },
  additionalSearchParameters: { query_by: "name" }
});

const search = instantsearch({ indexName: "products", searchClient: adapter.searchClient });
search.addWidgets([searchBox({ container: "#search" }), hits({ container: "#hits" })]);
search.start();
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High Availability 

# Start a 3-node cluster
typesense-server --data-dir /data --api-key=key --nodes /etc/typesense/nodes
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Automatic leader election, data replication, and failover.

Who Uses Typesense?

With 21K+ GitHub stars:

  • E-commerce platforms replacing Algolia
  • Documentation sites
  • Recipe and content search apps
  • SaaS products with search features

Get Started

  1. Run Docker container (one command)
  2. Create a collection with schema
  3. Index your documents
  4. Search with typo tolerance in <1ms

No JVM. No cluster configuration. Just fast search.

Need data to index in your search engine? Check out my web scraping tools on Apify — extract structured data from any website. Custom solutions: spinov001@gmail.com

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