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elasticsearch

Elasticsearch

JavaOpen SourceSelf-hostedManaged

The leading distributed search and analytics engine. Elasticsearch powers full-text search, log aggregation (ELK stack), and complex analytics queries at scale. Powerful but operationally complex to self-host.

License

SSPL / Elastic License

Language

Java

98
Trust
Excellent

Why Elasticsearch?

You need full-text search with complex filtering and faceting

You're building a log aggregation pipeline (ELK stack)

You need near-real-time analytics over large datasets

Signal Breakdown

What drives the Trust Score

npm downloads
3.8M / wk
Commits (90d)
891 commits
GitHub stars
70k ★
Stack Overflow
82k q's
Community
High
Weighted Trust Score98 / 100

Download Trend

Last 12 months

Tradeoffs & Caveats

Know before you commit

You need a simple hosted search (Algolia or Typesense are easier)

Your team can't manage cluster operations — use Elastic Cloud

You're doing vector search only — Pinecone or pgvector are better

Pricing

Free tier & paid plans

Free tier

Open-source self-host free · Cloud: 14-day trial

Paid

$95/mo Cloud entry (8GB RAM)

Elastic Cloud pricing per deployment

Often Used Together

Complementary tools that pair well with Elasticsearch

fastapi

FastAPI

Backend Frameworks

97Excellent
View
express

Express.js

Backend Frameworks

87Strong
View
kafka

Apache Kafka

Data Engineering

92Excellent
View
docker

Docker

DevOps & Infra

93Excellent
View
supabase

Supabase

Database & Cache

95Excellent
View

Learning Resources

Docs, videos, tutorials, and courses

Elasticsearch Docs

docs

GitHub repo

github

Elasticsearch quickstart

tutorial

Get Started

Repository and installation options

View on GitHub

github.com/elastic/elasticsearch

npmnpm install @elastic/elasticsearch
pippip install elasticsearch
dockerdocker run -p 9200:9200 elasticsearch:8.13.0

Quick Start

Copy and adapt to get going fast

import { Client } from '@elastic/elasticsearch';

const es = new Client({ node: process.env.ELASTICSEARCH_URL });

// Index a document
await es.index({ index: 'tools', id: '1', document: { name: 'Elasticsearch', category: 'search' } });

// Search
const { hits } = await es.search({
  index: 'tools',
  query: { multi_match: { query: 'search analytics', fields: ['name', 'summary'] } },
});
console.log(hits.hits.map(h => h._source));

Code Examples

Common usage patterns

Autocomplete with completion suggester

Build a fast autocomplete endpoint

// Create index with completion field
await es.indices.create({
  index: 'tools',
  mappings: {
    properties: {
      name: { type: 'text' },
      suggest: { type: 'completion' },
    },
  },
});

// Suggest query
const { suggest } = await es.search({
  index: 'tools',
  suggest: {
    tool_suggest: {
      prefix: 'ela',
      completion: { field: 'suggest', size: 5 },
    },
  },
});

Aggregations

Count tools by category

const result = await es.search({
  index: 'tools',
  size: 0,
  aggs: {
    by_category: {
      terms: { field: 'category.keyword', size: 20 },
      aggs: {
        avg_trust: { avg: { field: 'trust_score' } },
      },
    },
  },
});

const buckets = result.aggregations.by_category.buckets;

Bulk indexing

Index many documents efficiently in one request

const operations = tools.flatMap(tool => [
  { index: { _index: 'tools', _id: tool.id } },
  { name: tool.name, category: tool.category, trust_score: tool.trustScore },
]);

const result = await es.bulk({ refresh: true, operations });
if (result.errors) {
  console.error('Bulk errors:', result.items.filter(i => i.index?.error));
}

Community Notes

Real experiences from developers who've used this tool