Algolia聽vs聽Elasticsearch

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Algolia
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Algolia vs Elasticsearch: What are the differences?

Developers describe Algolia as "Developer-friendly API and complete set of tools for building search". 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. On the other hand, Elasticsearch is detailed as "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).

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

Some of the features offered by Algolia are:

  • Database search
  • Multi-attributes
  • Search as you type

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

"Ultra fast", "Super easy to implement" and "Easy setup, fast and relevant" are the key factors why developers consider Algolia; whereas "Powerful api", "Great search engine" and "Open source" are the primary reasons why Elasticsearch is favored.

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.

Uber Technologies, Instacart, and Slack are some of the popular companies that use Elasticsearch, whereas Algolia is used by Medium, StackShare, and Product Hunt. Elasticsearch has a broader approval, being mentioned in 2000 company stacks & 976 developers stacks; compared to Algolia, which is listed in 258 company stacks and 54 developer stacks.

- No public GitHub repository available -

What is 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.

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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Why do developers choose Algolia?
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What are some alternatives to Algolia 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.
Swiftype
Swiftype is the easiest way to add great search to your website or mobile application.
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.
Klevu
It is an intelligent site search solution designed to help eCommerce businesses increase onsite sales and improve the customer online shopping experience.
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 Algolia and Elasticsearch
Tim Specht
Tim Specht
鈥嶤o-Founder and CTO at Dubsmash | 16 upvotes 124.9K views
atDubsmashDubsmash
Elasticsearch
Elasticsearch
Algolia
Algolia
Memcached
Memcached
#SearchAsAService

Although we were using Elasticsearch in the beginning to power our in-app search, we moved this part of our processing over to Algolia a couple of months ago; this has proven to be a fantastic choice, letting us build search-related features with more confidence and speed.

Elasticsearch is only used for searching in internal tooling nowadays; hosting and running it reliably has been a task that took up too much time for us in the past and fine-tuning the results to reach a great user-experience was also never an easy task for us. With Algolia we can flexibly change ranking methods on the fly and can instead focus our time on fine-tuning the experience within our app.

Memcached is used in front of most of the API endpoints to cache responses in order to speed up response times and reduce server-costs on our side.

#SearchAsAService

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Julien DeFrance
Julien DeFrance
Principal Software Engineer at Tophatter | 16 upvotes 858.5K views
atSmartZipSmartZip