Apache Solr vs Sphinx
Overview
Detailed Comparison
It 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 it pretty much as with a database server. | It uses the tools you use to make application building a snap. It is built on the battle-tested Apache Zookeeper, it makes it easy to scale up and down. |
Output formats: HTML (including Windows HTML Help), LaTeX (for printable PDF versions), ePub, Texinfo, manual pages, plain text;Extensive cross-references: semantic markup and automatic links for functions, classes, citations, glossary terms and similar pieces of information;Hierarchical structure: easy definition of a document tree, with automatic links to siblings, parents and children;Automatic indices: general index as well as a language-specific module indices;Code handling: automatic highlighting using the Pygments highlighter;Extensions: automatic testing of code snippets, inclusion of docstrings from Python modules (API docs), and more | Advanced full-text search capabilities; Optimized for high volume traffic; Standards based open interfaces - XML, JSON and HTTP; Comprehensive administration interfaces; Easy monitoring; Highly scalable and fault tolerant; Flexible and adaptable with easy configuration |
Statistics | |
Stacks 906 | Stacks 139 |
Followers 300 | Followers 91 |
Votes 32 | Votes 0 |
Pros & Cons | |
Pros
| No community feedback yet |
Integrations | |
| No integrations available | |
What are some alternatives to Sphinx, Apache Solr?
MkDocs
It builds completely static HTML sites that you can host on GitHub pages, Amazon S3, or anywhere else you choose. There's a stack of good looking themes available. The built-in dev-server allows you to preview your documentation as you're writing it. It will even auto-reload and refresh your browser whenever you save your changes.
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.
Search the world's information, including webpages, images, videos and more. Google has many special features to help you find exactly what you're looking for.
YugabyteDB
An open-source, high-performance, distributed SQL database built for resilience and scale. Re-uses the upper half of PostgreSQL to offer advanced RDBMS features, architected to be fully distributed like Google Spanner.
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.
Qdrant
It is an open-source Vector Search Engine and Vector Database written in Rust. It deploys as an API service providing search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more.
Weaviate
It is an open-source vector search engine. It allows you to store data objects and vector embeddings from your favorite ML-models, and scale seamlessly into billions of data objects.
AddSearch
We help your website visitors find what they are looking for. AddSearch is a lightning fast, accurate and customizable site search engine with a Search API. AddSearch works on all devices and is easy to install, customize and tweak.
Carrot2
It organizes your search results into topics. With an instant overview of what's available, you will quickly find what you're looking for.
ArangoSearch
It is a C++ based full-text search engine including similarity ranking capabilities natively integrated into ArangoDB. It allows users to combine two information retrieval techniques: boolean and generalized ranking retrieval. Search results “approved” by the boolean model can be ranked by relevance to the respective query using the Vector Space Model in conjunction with BM25 or TFIDF weighting schemes.
