Elasticsearch vs. Azure Search



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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).

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.

Want advice about which of these to choose?Ask the StackShare community!

Why do developers choose Elasticsearch?
Why do you like Elasticsearch?

Why do developers choose Azure Search?
Why do you like Azure Search?

What are the cons of using Elasticsearch?
Downsides of Elasticsearch?

What are the cons of using Azure Search?
No Cons submitted yet for Azure Search
Downsides of Azure Search?

How much does Elasticsearch cost?
Elasticsearch Pricing
How much does Azure Search cost?
What companies use Elasticsearch?
2334 companies on StackShare use Elasticsearch
What companies use Azure Search?
11 companies on StackShare use Azure Search
What tools integrate with Elasticsearch?
29 tools on StackShare integrate with Elasticsearch
What tools integrate with Azure Search?
3 tools on StackShare integrate with Azure Search

What are some alternatives to Elasticsearch and Azure Search?

  • Algolia - Developer-friendly API and complete set of tools for building search
  • Amazon Elasticsearch Service - Real-time, distributed search and analytics engine that fits nicely into a cloud environment
  • Swiftype - Powerful and scalable search for any application or website
  • Amazon CloudSearch - Set up, manage, and scale a search solution for your website or application

See all alternatives to Elasticsearch

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Related Stack Decisions
Tim Specht
Tim Specht
‎Co-Founder and CTO at Dubsmash · | 16 upvotes · 3043 views
atDubsmash
Memcached
Algolia
Elasticsearch
#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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