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Hosted search-as-a-service platform delivering real-time, full-text search for apps and websites
Open-Source Projects
Discover top open-source software, updated regularly with real-world adoption signals.
Discover top open-source software, updated regularly with real-world adoption signals.
Blazing-fast multi-modal search platform built on Apache Lucene
Enterprise search platform powering full-text, vector, and geospatial search capabilities. Built on Apache Lucene, Solr delivers high-performance information retrieval for the world's largest organizations.
Apache Solr is a production-ready search platform that combines full-text search, vector search, and geospatial capabilities in a single solution. Built on the proven Apache Lucene foundation, Solr delivers the performance and scalability required by enterprise organizations managing massive data volumes.
Solr adapts to modern infrastructure with native support for Docker containers and Kubernetes orchestration through the official Solr Operator. Whether you're running a single-node development instance or a distributed SolrCloud cluster, the platform scales to meet your needs. The comprehensive Reference Guide walks teams through deployment scenarios from proof-of-concept to production.
The platform includes multiple example configurations—from schema-less indexing to comprehensive techproducts demonstrations—that accelerate development cycles. Teams can start with sensible defaults and progressively customize as requirements evolve. Built with Java and Gradle, Solr integrates naturally into JVM-based technology stacks while offering REST APIs for polyglot environments.
When teams consider Apache Solr, these hosted platforms usually appear on the same shortlist.
Hosted search-as-a-service platform delivering real-time, full-text search for apps and websites
Managed search service to index and query text & structured data
AI-powered enterprise search service that indexes and searches across various content repositories with natural language queries
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
E-commerce Product Catalog Search
Enable customers to find products through full-text queries, faceted navigation, and geospatial filtering for location-based inventory
Enterprise Knowledge Management
Index documents, wikis, and internal resources with relevance tuning and access controls for organization-wide information retrieval
Semantic Search with Vector Embeddings
Implement AI-powered search using vector representations to surface conceptually similar content beyond keyword matching
Real-time Analytics Dashboard
Aggregate and query time-series data with faceting and grouping for interactive business intelligence visualizations
Both are built on Lucene, but Solr emphasizes configurability and traditional search use cases, while Elasticsearch focuses on analytics and log aggregation. Solr offers stronger SQL support and more mature faceting capabilities.
Yes, Solr supports vector search capabilities, enabling semantic search and similarity matching using embeddings from machine learning models alongside traditional full-text search.
SolrCloud provides distributed indexing and querying with automatic failover, replication, and load balancing across multiple nodes. Standalone Solr runs on a single server without built-in clustering.
Solr requires a JVM environment (Java 11+). For production, consider SolrCloud with ZooKeeper for coordination, adequate RAM for caching, and SSD storage. Docker and Kubernetes deployments are officially supported.
Yes, Solr can infer schema from incoming data during indexing, allowing rapid prototyping. You can also define explicit schemas for production use cases requiring strict data validation and optimization.
Project at a glance
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