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Open-Source Databases · apache

solr

Apache Solr is an open-source search engine built on Apache Lucene that handles full-text, vector, and geospatial search at scale. It's a mature Java project widely used in enterprise environments and supports deployment on standard infrastructure, Docker, and Kubernetes.

Source: GitHub — github.com/apache/solr
1.6k
GitHub stars
842
Forks
Java
Primary language
Apache-2.0
License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

FieldValue
Repositoryapache/solr
Ownerapache
Primary languageJava
LicenseApache-2.0 — OSI-approved
Stars1.6k
Forks842
Open issues167
Latest releaseUnknown
Last updated2026-07-07
Sourcehttps://github.com/apache/solr

What solr is

Solr is a distributed search platform written in Java that leverages Lucene for indexing and querying. It provides REST APIs, supports multi-modal search (text, vector, spatial), and includes SolrCloud for distributed indexing and fault tolerance.

Quickstart

Get the solr source

Clone the repository and explore it locally.

terminalbash
git clone https://github.com/apache/solr.gitcd solr# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Enterprise Full-Text Search

Solr excels at powering site search, document retrieval, and content discovery across large document repositories. Suitable for organizations needing production-grade search with faceting, filtering, and relevance tuning.

Multi-Modal Search at Scale

Combine full-text, vector embeddings, and geospatial queries in a single platform. Ideal for e-commerce, knowledge bases, and recommendation systems requiring hybrid search capabilities.

Distributed Cloud Search Infrastructure

SolrCloud provides horizontal scalability, replication, and automatic failover. Suited for high-volume indexing and query loads with Kubernetes or Docker deployment models.

Implementation considerations

  • JVM heap sizing and garbage collection tuning are critical for query latency and stability; default configs require adjustment for production workloads.
  • Schema design (field types, analyzers, copyFields) directly impacts search quality and must be planned before indexing large datasets.
  • Distributed mode (SolrCloud) introduces operational complexity; single-node Solr is simpler but lacks fault tolerance and horizontal scaling.
  • Reindexing strategy needed when schema changes are required; plan backup and alias-based rollover processes.
  • Monitoring and alerting (metrics via JMX or HTTP APIs) are essential; native observability limited—integration with external systems (Prometheus, ELK) recommended.

When to avoid it — and what to weigh

  • Simple Key-Value Lookups — Solr adds operational overhead for use cases better served by caching layers (Redis) or transactional databases. Not optimized for point lookups without search semantics.
  • Real-Time Transactions — Solr is eventually consistent; document updates are indexed asynchronously. Avoid if you need ACID guarantees or immediate consistency across reads and writes.
  • Lightweight, Embedded Scenarios — Solr is a server requiring JVM heap, separate process management, and operational tooling. Consider embedded alternatives (Lucene directly, SQLite FTS) for simple embedded use cases.
  • Minimal Operations Capacity — SolrCloud cluster management, JVM tuning, and monitoring require DevOps expertise. Teams without search platform experience may find deployment and troubleshooting complex.

License & commercial use

Licensed under Apache License 2.0 (Apache-2.0), a permissive OSI-approved license granting rights to use, modify, and distribute.

Apache-2.0 permits commercial use without royalties or vendor lock-in. Attribution and license notice must be included. No vendor support or SLA included in open-source; commercial support available through ASF-affiliated consultants. Verify terms with legal counsel for mission-critical deployments.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

SignalAssessment
MaintenanceActive
DocumentationStrong
License clarityClear
Deployment complexityHigh
DEV.co fitGood
Assessment confidenceHigh
Security considerations

No exploit details provided in data. Consider: default Solr installations have no authentication (open to LAN); production deployments must enable auth, network isolation, and TLS. JVM memory exposure (heap dumps), query injection via unsanitized input parameters. Run Solr on JDK with latest security patches. Refer to Solr security guide and Apache advisories before production deployment.

Alternatives to consider

Elasticsearch

Elastic-licensed, closed-source model; stronger out-of-box observability and automatic sharding. Steeper licensing costs at scale; consider if you need managed SaaS or prefer vendor ecosystem.

Meilisearch

Lightweight, simpler API, optimized for typo tolerance and relevance tuning. Lacks distributed mode and multi-modal search; better for greenfield projects with smaller scale needs.

OpenSearch

Open-source Elasticsearch fork (SSPL/Elastic License dual-licensed). Community-driven alternative if concerned about Elastic's licensing direction; API compatible with Elasticsearch.

Software development agency

Build on solr with DEV.co software developers

Let our search and cloud infrastructure experts guide your deployment. We'll assess schema design, SolrCloud topology, and operational readiness to ensure production stability.

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solr FAQ

Do I need ZooKeeper for Solr?
Not for single-node Solr. SolrCloud (distributed mode) requires ZooKeeper for cluster coordination; most production setups use ZooKeeper. Version 9.2+ has experimental Raft-based mode without external coordination.
How long does it take to index 1 billion documents?
Unknown from GitHub data. Depends on document size, hardware, network latency, analyzer complexity, and parallelism. Benchmarking required for your schema and infrastructure.
Can Solr replace my primary database?
No. Solr is a search index, not a durable store. Use a primary database (PostgreSQL, MongoDB) for authoritative data and sync to Solr for search. Data loss may occur during cluster changes.
What JVM version should I use?
Refer to the official system requirements (linked in README). Generally, a recent LTS JDK (11, 17, 21) with latest security patches. Test thoroughly before production deployment.

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