Opensolr Platform Documentation - Complete User Guide

Everything you need to master the Opensolr platform

Website POST /api REST API Database Opensolr Search Index Search Results Analytics AI Vectors AI & Vectors

Welcome to the Opensolr Documentation

Everything you need to build, manage, and scale search for your application — from your first index to production-ready search in minutes. For a comprehensive walkthrough of the entire platform, see The Complete Opensolr Platform Guide.

What is Opensolr?

Opensolr is a fully managed Apache Solr hosting platform. Think of it as your own private search engine, running in the cloud, ready in seconds. You do not need to install software, manage servers, or worry about uptime. You create an index, put your data in, and search it. To understand how the platform works under the hood, read How Does Opensolr Work?

Whether you are building search for a website, an e-commerce store, a mobile app, or anything else that needs fast, relevant results, Opensolr handles the infrastructure so you can focus on your product.

Quick Start

Get from zero to search results in under five minutes. Follow these steps in order.

1 Sign Up 2 Create Index 3 Add Data 4 Search 5 Customize
  1. Create your free account at opensolr.com/signup. No credit card required. You get a free index to experiment with immediately. Need a step-by-step walkthrough? Follow the Getting Started guide.
  2. Create your first index. Pick a name, choose a server region, and select an index type (Generic, Ecommerce, or Drupal). Full guide here.
  3. Add your data. Use the Web Crawler to automatically pull in website pages, or push documents via the Data Ingestion API.
  4. Run your first search. Open the Solr Query tab in your dashboard and type a keyword. You will see results instantly. If your index uses the web crawler schema (web crawler, Drupal module, or WordPress plugin indexes), you can also use the built-in hosted search page.
  5. Customize and go live. Configure facet filters, tweak search relevance, set up security, and embed search into your application.

Choose Your Path

Different people need different things. Pick the path that matches you best.

YOU Developer API, code examples, schema config Business Owner Crawler, dashboard, analytics Coming from Elasticsearch Migration tips, comparison

I am a Developer

You want to integrate Opensolr into your app with code. Start here:

I am a Business Owner

You want search on your website without writing code. Start here:

I am Coming from Elasticsearch

Migrating from Elasticsearch or another search platform? The concepts map closely:

Key Concepts

A few terms you will see throughout this documentation, explained in plain language.

Opensolr Index

An index is where your searchable data lives. Think of it as a database table optimized for searching. You create one index per project or application. Some people call this a "collection" or "core" — in Opensolr, it is always called an index.

Document

A document is a single record in your index. It could be a blog post, a product listing, a web page, or anything else. Each document has fields like "title", "description", "price", etc.

Query

A query is a search request. When a user types "red shoes size 10" into a search box, that text is sent to Opensolr as a query. Opensolr finds the best matching documents and returns them ranked by relevance.

Facet

A facet is a filter category shown alongside search results. For example, on an e-commerce site, facets might include "Brand", "Price Range", and "Color". Users click facets to narrow results without typing a new query.

Using a CMS? Start with the Integration

If your site runs on Drupal or WordPress, you do not need to wire up Solr manually. Opensolr ships dedicated connectors for both — they handle credentials, config files, schema, and indexing automatically. Skip the rest of this documentation for now and go straight to the integration that matches your stack.

No persistent AI. No telemetry. Just smarter Solr.

Opensolr does not run a persistent AI model on your data, does not phone home, and does not collect telemetry from your site. The "vector search" you see across these docs is dense vector embeddings — a one-time mathematical fingerprint of each document that lets classic Solr keyword search also match by meaning. Any optional LLM add-ons (answer summaries, document readers) sit on top and can be disabled entirely.

Need help?

If you get stuck at any point, email support@opensolr.com and a real person will reply. You can also check the Knowledge Base for quick answers to common questions.