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Average Ratings 0 Ratings

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ease
features
design
support

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Description

Redis Enterprise offers a robust real-time indexing, querying, and full-text search engine that is accessible both on-premises and as a cloud-managed service. This real-time search capability is optimized for rapid indexing and data ingestion, utilizing high-performance in-memory data structures developed in C. You can expand and partition indexes across multiple shards and nodes, enhancing both speed and memory capacity. With an impressive five-nines availability and Active-Active failover, uninterrupted operations are ensured in any circumstance. The real-time search feature of Redis Enterprise enables users to swiftly establish primary and secondary indexes on Hash and JSON datasets through an incremental indexing method, which facilitates quick index creation and removal. These indexes empower users to perform queries at remarkable speeds, execute complex aggregations, and filter data based on properties, numeric ranges, and geographical distances, thus enhancing overall data accessibility. By leveraging these capabilities, organizations can significantly improve their data management and retrieval processes.

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

Screenshots View All

Screenshots View All

Integrations

Acontext
Archon Data Store
Camunda
Crowdin
Dash
Lygos
Mermaid Chart
MySQL
PushFeedback
Read the Docs
Redis

Integrations

Acontext
Archon Data Store
Camunda
Crowdin
Dash
Lygos
Mermaid Chart
MySQL
PushFeedback
Read the Docs
Redis

Pricing Details

No price information available.
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

Redis

Country

United States

Website

redis.com/modules/redis-search/

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

Alternatives

Alternatives

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