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Description

The Apache Lucene™ initiative is dedicated to creating open-source search technology. This initiative not only offers a fundamental library known as Lucene™ core but also includes PyLucene, which serves as a Python interface for Lucene. Lucene Core functions as a Java library that delivers robust features for indexing and searching, including capabilities for spellchecking, hit highlighting, and sophisticated analysis/tokenization. The PyLucene project enhances accessibility by allowing developers to utilize Lucene Core through Python. Backing this initiative is the Apache Software Foundation, which supports a variety of open-source software endeavors. Notably, Apache Lucene is made available under a license that is favorable for commercial use. It has established itself as a benchmark for search and indexing efficiency. Furthermore, Lucene is the foundational search engine for both Apache Solr™ and Elasticsearch™, which are widely used in various applications. From mobile platforms to major websites like Twitter, Apple, and Wikipedia, our core algorithms, together with the Solr search server, enable a multitude of applications globally. Ultimately, the objective of Apache Lucene is to deliver exceptional search capabilities that meet the needs of diverse users. Its continuous development reflects the commitment to innovation in search technology.

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.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Acontext
Apache Solr
Apache Usergrid
Archon Data Store
Camunda
Elasticsearch
Lygos
Redis

Integrations

Acontext
Apache Solr
Apache Usergrid
Archon Data Store
Camunda
Elasticsearch
Lygos
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

Apache Software Foundation

Founded

1999

Country

United States

Website

lucene.apache.org

Vendor Details

Company Name

Redis

Country

United States

Website

redis.com/modules/redis-search/

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

Redis Reviews

Redis

Redis Labs