Azure Search vs Elasticsearch

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Azure Search

61
165
+ 1
16
Elasticsearch

22.2K
16.3K
+ 1
1.6K
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Azure Search vs Elasticsearch: What are the differences?

Azure Search: 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; Elasticsearch: Open Source, Distributed, RESTful Search Engine. 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).

Azure Search and Elasticsearch can be categorized as "Search as a Service" tools.

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, Elasticsearch provides the following key features:

  • Distributed and Highly Available Search Engine.
  • Multi Tenant with Multi Types.
  • Various set of APIs including RESTful

"Easy to set up" is the primary reason why developers consider Azure Search over the competitors, whereas "Powerful api" was stated as the key factor in picking Elasticsearch.

Elasticsearch is an open source tool with 42.4K GitHub stars and 14.2K GitHub forks. Here's a link to Elasticsearch's open source repository on GitHub.

Pros of Azure Search
Pros of Elasticsearch
  • 4
    Easy to set up
  • 3
    Managed
  • 3
    Auto-Scaling
  • 2
    Easy Setup
  • 2
    More languages
  • 2
    Lucene based search criteria
  • 320
    Powerful api
  • 310
    Great search engine
  • 230
    Open source
  • 213
    Restful
  • 200
    Near real-time search
  • 96
    Free
  • 83
    Search everything
  • 54
    Easy to get started
  • 45
    Analytics
  • 26
    Distributed
  • 6
    Fast search
  • 5
    More than a search engine
  • 3
    Awesome, great tool
  • 3
    Easy to scale
  • 3
    Great docs
  • 2
    Nosql DB
  • 2
    Great piece of software
  • 2
    Document Store
  • 2
    Great customer support
  • 2
    Intuitive API
  • 2
    Fast
  • 2
    Easy setup
  • 2
    Highly Available
  • 1
    Not stable
  • 1
    Reliable
  • 1
    Github
  • 1
    Elaticsearch
  • 1
    Actively developing
  • 1
    Responsive maintainers on GitHub
  • 1
    Ecosystem
  • 1
    Scalability
  • 1
    Potato
  • 0
    Community
  • 0
    Easy to get hot data

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Cons of Azure Search
Cons of Elasticsearch
    Be the first to leave a con
    • 6
      Diffecult to get started
    • 5
      Resource hungry
    • 4
      Expensive
    • 3
      Hard to keep stable at large scale

    Sign up to add or upvote consMake informed product decisions

    - 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 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).

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    What companies use Azure Search?
    What companies use Elasticsearch?

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    What tools integrate with Azure Search?
    What tools integrate with Elasticsearch?

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    Blog Posts

    May 21 2019 at 12:20AM
    https://img.stackshare.io/stack/370781/default_a990c1c91c00f9e31ddef32a6738f0f105af38dd.png logo

    Elastic

    ElasticsearchKibanaLogstash+4
    11
    2584
    GitHubPythonReact+42
    46
    38551
    GitHubPythonNode.js+47
    43
    67731
    GitHubGitGoogle Analytics+30
    25
    14378
    JavaScriptGitHubjQuery+26
    18
    4520
    What are some alternatives to Azure Search and Elasticsearch?
    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.
    Apache Solr
    It uses the tools you use to make application building a snap. It is built on the battle-tested Apache Zookeeper, it makes it easy to scale up and down.
    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.
    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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