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An open source enterprise search server based on Lucene search library, with XML/HTTP and JSON APIs, hit highlighting, faceted search, caching, replication etc.

What is Solr?

Solr is the popular, blazing fast open source enterprise search platform from the Apache Lucene project. Its major features include powerful full-text search, hit highlighting, faceted search, near real-time indexing, dynamic clustering, database integration, rich document (e.g., Word, PDF) handling, and geospatial search. Solr is highly reliable, scalable and fault tolerant, providing distributed indexing, replication and load-balanced querying, automated failover and recovery, centralized configuration and more. Solr powers the search and navigation features of many of the world's largest internet sites.
Solr is a tool in the Search Engines category of a tech stack.

Who uses Solr?

Companies
138 companies use Solr in their tech stacks, including SendGrid, SurveyMonkey, and GoGuardian.

Developers
40 developers use Solr.

Solr Integrations

Server Density, Datadog, Lucene, ContainerShip, and Netuitive are some of the popular tools that integrate with Solr. Here's a list of all 5 tools that integrate with Solr.

Why developers like Solr?

Here’s a list of reasons why companies and developers use Solr
Solr Reviews

Here are some stack decisions, common use cases and reviews by companies and developers who chose Solr in their tech stack.

Ganesa Vijayakumar
Ganesa Vijayakumar
Full Stack Coder | Module Lead · | 15 upvotes · 39.6K views
SonarQube
Codacy
Docker
Git
Apache Maven
Amazon EC2 Container Service
Microsoft Azure
Amazon Route 53
Elasticsearch
Solr
Amazon RDS
Amazon S3
Heroku
Hibernate
MySQL
Node.js
Java
Bootstrap
jQuery Mobile
jQuery UI
jQuery
JavaScript
React Native
React Router
React

I'm planning to create a web application and also a mobile application to provide a very good shopping experience to the end customers. Shortly, my application will be aggregate the product details from difference sources and giving a clear picture to the user that when and where to buy that product with best in Quality and cost.

I have planned to develop this in many milestones for adding N number of features and I have picked my first part to complete the core part (aggregate the product details from different sources).

As per my work experience and knowledge, I have chosen the followings stacks to this mission.

UI: I would like to develop this application using React, React Router and React Native since I'm a little bit familiar on this and also most importantly these will help on developing both web and mobile apps. In addition, I'm gonna use the stacks JavaScript, jQuery, jQuery UI, jQuery Mobile, Bootstrap wherever required.

Service: I have planned to use Java as the main business layer language as I have 7+ years of experience on this I believe I can do better work using Java than other languages. In addition, I'm thinking to use the stacks Node.js.

Database and ORM: I'm gonna pick MySQL as DB and Hibernate as ORM since I have a piece of good knowledge and also work experience on this combination.

Search Engine: I need to deal with a large amount of product data and it's in-detailed info to provide enough details to end user at the same time I need to focus on the performance area too. so I have decided to use Solr as a search engine for product search and suggestions. In addition, I'm thinking to replace Solr by Elasticsearch once explored/reviewed enough about Elasticsearch.

Host: As of now, my plan to complete the application with decent features first and deploy it in a free hosting environment like Docker and Heroku and then once it is stable then I have planned to use the AWS products Amazon S3, EC2, Amazon RDS and Amazon Route 53. I'm not sure about Microsoft Azure that what is the specialty in it than Heroku and Amazon EC2 Container Service. Anyhow, I will do explore these once again and pick the best suite one for my requirement once I reached this level.

Build and Repositories: I have decided to choose Apache Maven and Git as these are my favorites and also so popular on respectively build and repositories.

Additional Utilities :) - I would like to choose Codacy for code review as their Startup plan will be very helpful to this application. I'm already experienced with Google CheckStyle and SonarQube even I'm looking something on Codacy.

Happy Coding! Suggestions are welcome! :)

Thanks, Ganesa

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Poogles
Poogles
| 1 upvotes · 536 views
atThe Independent
Solr

Full text search is provided by a SOLR cluster. This is done on Master/Slave replication with Varnish as a cache. Solr

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Solr

elastic search 와 함께 유명한 검색 엔진 오픈 소스 중 하나 이다. 처음 설정할 것이 많은데, 어플리케이션의 이해가 없다면 잦은 수정이 필요하다. Solr Client 로 제어 할 수 없고 Server 에서 설정해 줘야하는 것들이 있어 서버 설정하는 부분이 중요하다. 서버 설정만 잘 되있다면, Client 쪽 소스는 별게 없다.

중요한 건 형태소 분석기.... Solr

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Solr's features

  • Advanced Full-Text Search Capabilities
  • Optimized for High Volume Web Traffic
  • Standards Based Open Interfaces - XML, JSON and HTTP
  • Comprehensive HTML Administration Interfaces
  • Server statistics exposed over JMX for monitoring
  • Linearly scalable, auto index replication, auto failover and recovery
  • Near Real-time indexing
  • Flexible and Adaptable with XML configuration
  • Extensible Plugin Architecture

Solr Alternatives & Comparisons

What are some alternatives to Solr?
Lucene
Lucene Core, our flagship sub-project, provides Java-based indexing and search technology, as well as spellchecking, hit highlighting and advanced analysis/tokenization capabilities.
Algolia
Our mission is to make you a search expert. Push data to our API to make it searchable in real time. Build your dream front end with one of our web or mobile UI libraries. Tune relevance and get analytics right from your dashboard.
Elasticsearch
Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
Sphinx
Sphinx lets you either batch index and search data stored in an SQL database, NoSQL storage, or just files quickly and easily — or index and search data on the fly, working with Sphinx pretty much as with a database server. A variety of text processing features enable fine-tuning Sphinx for your particular application requirements, and a number of relevance functions ensures you can tweak search quality as well.
Searchkick
Searchkick learns what your users are looking for. As more people search, it gets smarter and the results get better. It’s friendly for developers - and magical for your users.
See all alternatives

Solr's Stats

- No public GitHub repository available -