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Average Ratings 0 Ratings
Description
Amazon Kendra is an exceptionally precise and user-friendly enterprise search solution driven by machine learning technology. It provides robust natural language search functionalities for your websites and applications, allowing users to effortlessly locate the information they require amidst the extensive content available within your organization. By utilizing natural language inquiries rather than merely basic keywords, you can obtain the information you seek, whether it be specific answers, frequently asked questions, or complete documents. This eliminates the frustration of navigating through lengthy lists of links in hopes of finding relevant information. Say farewell to information silos, as Kendra enables seamless integration of content from various sources such as file systems, SharePoint, intranet sites, and file sharing services into a unified location, facilitating swift searches for optimal answers. Over time, the accuracy of your search results improves, thanks to Kendra's machine learning algorithms, which adapt to understand and prioritize the most valuable results for your users. This continual enhancement ensures that users consistently receive the most relevant and useful information with every search query they perform.
Description
Sphinx is a high-performance open-source full-text search engine specifically designed to prioritize efficiency, search quality, and ease of integration. Built using C++, it operates seamlessly across various platforms including Linux (such as RedHat and Ubuntu), Windows, MacOS, Solaris, FreeBSD, and several others. Sphinx supports both batch indexing and on-the-fly searching of data from SQL databases, NoSQL systems, or even plain files, allowing for a flexible approach similar to querying a traditional database server. The platform offers numerous text processing capabilities that facilitate the customization of its functions to meet the distinct needs of different applications, while multiple relevance tuning options help enhance the quality of search results. Implementing searches through SphinxAPI requires only three lines of code, and using SphinxQL is even more straightforward, enabling users to write search queries in familiar SQL syntax. Remarkably, Sphinx can index between 10 to 15 MB of text in a second for each CPU core, translating to over 60 MB per second on a dedicated indexing server. With its robust features and efficient performance, Sphinx stands out as an excellent choice for developers seeking a search solution tailored to their specific requirements.
API Access
Has API
API Access
Has API
Integrations
AWS AI Services
Amazon Transcribe
Amazon Web Services (AWS)
BA Insight
Crowdin
Dash
Mermaid Chart
Microsoft SharePoint
MySQL
PushFeedback
Integrations
AWS AI Services
Amazon Transcribe
Amazon Web Services (AWS)
BA Insight
Crowdin
Dash
Mermaid Chart
Microsoft SharePoint
MySQL
PushFeedback
Pricing Details
$2.50 per hour
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/kendra/
Vendor Details
Company Name
Sphinx
Founded
2007
Country
United States
Website
sphinxsearch.com
Product Features
Enterprise Search
AI / Machine Learning
Faceted Search / Filtering
Full Text Search
Fuzzy Search
Indexing
Text Analytics
eDiscovery
Product Features
Enterprise Search
AI / Machine Learning
Faceted Search / Filtering
Full Text Search
Fuzzy Search
Indexing
Text Analytics
eDiscovery