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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.
Pros of Algolia
- Ultra fast125
- Super easy to implement95
- Modern search engine73
- Excellent support71
- Easy setup, fast and relevant70
- Typos handling46
- Search analytics40
- Designed to search records, not pages31
- Multiple datacenters30
- Distributed Search Network30
- Smart Highlighting10
- Search as you type9
- Instantsearch.js8
- Multi-attributes8
- Super fast, easy to set up6
- Amazing uptime5
- Database search5
- Realtime4
- Great documentation4
- Highly customizable4
- Github-awesome-autocomple4
- Powerful Search3
- Beautiful UI3
- Places.js3
- Integrates with just about everything2
- Awesome aanltiycs and typos hnadling2
- Fast response time1
- Smooth platform1
- Github integration1
- Developer-friendly frontend libraries1
Pros of Elasticsearch
- Powerful api320
- Great search engine310
- Open source230
- Restful213
- Near real-time search200
- Free96
- Search everything83
- Easy to get started54
- Analytics45
- Distributed26
- Fast search6
- More than a search engine5
- Awesome, great tool3
- Easy to scale3
- Great docs3
- Nosql DB2
- Great piece of software2
- Document Store2
- Great customer support2
- Intuitive API2
- Fast2
- Easy setup2
- Highly Available2
- Not stable1
- Reliable1
- Github1
- Elaticsearch1
- Actively developing1
- Responsive maintainers on GitHub1
- Ecosystem1
- Scalability1
- Potato1
- Community0
- Easy to get hot data0
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Cons of Algolia
- Expensive10
Cons of Elasticsearch
- Diffecult to get started6
- Resource hungry5
- Expensive4
- Hard to keep stable at large scale3