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Azure Search
Azure Search

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41
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15
Lucene
Lucene

110
86
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0
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Azure Search vs Lucene: What are the differences?

Developers describe Azure Search as "Search-as-a-service for web and mobile app development". Azure Search makes it easy to add powerful and sophisticated search capabilities to your website or application. Quickly and easily tune search results and construct rich, fine-tuned ranking models to tie search results to business goals. Reliable throughput and storage provide fast search indexing and querying to support time-sensitive search scenarios. On the other hand, Lucene is detailed as "A high-performance, full-featured text search engine library written entirely in Java". Lucene Core, our flagship sub-project, provides Java-based indexing and search technology, as well as spellchecking, hit highlighting and advanced analysis/tokenization capabilities.

Azure Search and Lucene are primarily classified as "Search as a Service" and "Search Engines" tools respectively.

Some of the features offered by Azure Search are:

  • Powerful, reliable performance
  • Easily tune search indices to meet business goals
  • Scale out simply

On the other hand, Lucene provides the following key features:

  • over 150GB/hour on modern hardware
  • small RAM requirements -- only 1MB heap
  • incremental indexing as fast as batch indexing
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- No public GitHub repository available -

What is Azure Search?

Azure Search makes it easy to add powerful and sophisticated search capabilities to your website or application. Quickly and easily tune search results and construct rich, fine-tuned ranking models to tie search results to business goals. Reliable throughput and storage provide fast search indexing and querying to support time-sensitive search scenarios.

What is 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.
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        What are some alternatives to Azure Search and Lucene?
        Elasticsearch
        Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
        Solr
        Solr is the popular, blazing fast open source enterprise search platform from the Apache Lucene project. Its major features include powerful full-text search, hit highlighting, faceted search, near real-time indexing, dynamic clustering, database integration, rich document (e.g., Word, PDF) handling, and geospatial search. Solr is highly reliable, scalable and fault tolerant, providing distributed indexing, replication and load-balanced querying, automated failover and recovery, centralized configuration and more. Solr powers the search and navigation features of many of the world's largest internet sites.
        Amazon CloudSearch
        Amazon CloudSearch enables you to search large collections of data such as web pages, document files, forum posts, or product information. With a few clicks in the AWS Management Console, you can create a search domain, upload the data you want to make searchable to Amazon CloudSearch, and the search service automatically provisions the required technology resources and deploys a highly tuned search index.
        Algolia
        Our mission is to make you a search expert. Push data to our API to make it searchable in real time. Build your dream front end with one of our web or mobile UI libraries. Tune relevance and get analytics right from your dashboard.
        Amazon Elasticsearch Service
        Amazon Elasticsearch Service is a fully managed service that makes it easy for you to deploy, secure, and operate Elasticsearch at scale with zero down time.
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        Decisions about Azure Search and Lucene
        StackShare Editors
        StackShare Editors
        Lucene
        Lucene
        Solr
        Solr

        "Slack provides two strategies for searching: Recent and Relevant. Recent search finds the messages that match all terms and presents them in reverse chronological order. If a user is trying to recall something that just happened, Recent is a useful presentation of the results.

        Relevant search relaxes the age constraint and takes into account the Lucene score of the document — how well it matches the query terms (Solr powers search at Slack). Used about 17% of the time, Relevant search performed slightly worse than Recent according to the search quality metrics we measured: the number of clicks per search and the click-through rate of the search results in the top several positions. We recognized that Relevant search could benefit from using the user’s interaction history with channels and other users — their ‘work graph’."

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        Interest over time
        Reviews of Azure Search and Lucene
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        How developers use Azure Search and Lucene
        Avatar of Blue Kangaroo
        Blue Kangaroo uses LuceneLucene

        High-performance text-based category classification.

        Avatar of nextdocdev
        nextdocdev uses Azure SearchAzure Search

        Used to build a mechanism to find the documents

        Avatar of Chris Riley
        Chris Riley uses Azure SearchAzure Search

        Application Global Search

        How much does Azure Search cost?
        How much does Lucene cost?
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