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What is Sphinx?

Sphinx is an efficient, open-source full-text search engine crafted to enhance search quality, performance, and integration ease. Developed in C++, it is compatible with a variety of operating systems, including Linux distributions like RedHat and Ubuntu, as well as Windows, MacOS, Solaris, FreeBSD, and more. The engine accommodates both batch indexing and real-time data searching from SQL databases, NoSQL sources, or even simple files, offering a versatile querying experience akin to that of a standard database server. With numerous text processing tools available, users can tailor its features to align with the unique needs of their applications, and various relevance tuning options significantly improve the quality of search outcomes. SphinxAPI necessitates just three lines of code to perform searches, while SphinxQL allows users to craft queries using familiar SQL syntax, making the process even easier. Impressively, Sphinx can index between 10 to 15 MB of text per second for each CPU core, resulting in indexing speeds exceeding 60 MB per second on dedicated servers. Given its extensive capabilities and high efficiency, Sphinx emerges as a top-tier option for developers looking for a customizable search solution that meets their specific demands, ultimately enhancing user experience in their applications.

What is Hound?

Hound is an exceptionally fast tool for searching through source code. It is built on the principles outlined in an article and the corresponding code created by Russ Cox, which focuses on using a trigram index for regular expression matching. The application comprises a static frontend developed in React that interacts with a Go backend, which is tasked with keeping the index updated for all repositories and executing searches through an efficient API. While Hound has mostly undergone testing on MacOS and CentOS, it is intended to work seamlessly on any Unix-like operating system. Although it does not officially support Windows, there are user reports suggesting that it compiles and operates well on that platform; for optimal performance, it is recommended to keep your data folder outside of the Windows Search Indexer. Users have shown great enthusiasm for its features, and the development team is actively working to improve its compatibility across more operating systems. This ongoing enhancement process is aimed at expanding Hound's usability and ensuring a smoother experience for a wider range of users.

Media

Media

Integrations Supported

Crowdin
Dash
Emacs
Mermaid Chart
MySQL
PushFeedback
Read the Docs
Sublime Text
Vim
Visual Studio Code

Integrations Supported

Crowdin
Dash
Emacs
Mermaid Chart
MySQL
PushFeedback
Read the Docs
Sublime Text
Vim
Visual Studio Code

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Sphinx

Date Founded

2007

Company Location

United States

Company Website

sphinxsearch.com

Company Facts

Organization Name

Etsy

Company Website

github.com/hound-search/hound

Categories and Features

Enterprise Search

AI / Machine Learning
Faceted Search / Filtering
Full Text Search
Fuzzy Search
Indexing
Text Analytics
eDiscovery

Categories and Features

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