CookieDev
Search solutions for your project (Algolia and co.)
4 min to read

In this article, we'll take a look at some really popular, renowned solutions and try to do a small comparison that might help you to choose the right one for your website or application. Products for today's review are:
  • Algolia,
  • Elasticsearch,
  • Microsoft Azure Search,
  • Apache SOLR,
  • Lucidworks Fusion,
  • And some other engines briefly
Algolia

Algolia appeared in far 2012 and since that time lots of companies, even business giants like Slack and Zendesk, have their preference for this technology. Algolia offers a wide range of solutions for various business areas and communication channels: websites, applications, voice assistants, etc. Algolia takes into account the context and type of query, possible typos, synonyms, and word forms, query input in different languages, and much more.

It also allows you to set up a strategy for ranking search results based on geo-data and user preferences. The other feature is the instant search when the results are shown to you as you type in the search box. And finally, Algolia offers front-end components for iOS, Android, and mobile web. Developers say that Algolia has a simple and powerful API that integrates this solution and quickly sets it up for most client needs.

For today Algolia is a hosted SaaS full-featured search solution. It can be used for free if you need up to 1000 requests a day. If our users make up to 100 000 requests per month service will ask for authentication, but still, be free. And after that quantity, we'll pay $0.40 for 1000 requests or create an individual unlimited plan.

Algolia has API for clients on PHP, Ruby, Javascript, Python, Swift, Kotlin, .NET, and other popular languages and technologies. It also can be easily integrated into Ruby on Rails, Symphony, Django, and Laravel. And we should not forget about CMS integration. Among them are Magento, WordPress, Shopify, and Zendesk.

Elasticsearch (vs Algolia)

Another search engine solution also used by big (and small) businesses is Elasticsearch. It is a distributed search and analytics engine based on the Apache Lucene library. Elasticsearch was firstly released in 2010, and very soon became the most popular search solution. Today companies like Wikipedia, Github, and Facebook use it for a variety of purposes.

Elasticsearch is commonly used for full-text search, security systems, business analytics, and ongoing process monitoring. It also has a satellite product Kibana for data visualization and creating interactive dashboards. And if you need log analysis you'll have to use a third product called Logstash. The stack of these products is usually called the ELK stack. And there is a certain difference between Elasticsearch and Algolia because Algolia provides all functionality in one package.

In fact, many developers affirm that using Algolia you can build a full featured search in a few days while using Elasticsearch you will achieve this only with additional time and investments. But actually, both solutions are loved by their customers and give them lots of opportunities.

Elasticsearch offers simple REST-based APIs, and a lightweight HTTP interface, and uses schemaless JSON documents, making it easier to get started and quickly build applications for a variety of use cases. By the way, you may use open source plugins, such as language parsers and recommendation engines to extend the functionality of your application.

In the same way, Algolia Elasticsearch has its API for Java, Python, PHP, JavaScript, Node.js, Ruby, and many other languages and technologies. So you may use it to create a search module even from scratch.

If we talk about pricing, there is a SaaS service https://elastic.co that gives access to the functionality of ELK. For today prices on this site start at $95 per month.
Tetiana Holovchenko
Co-founder, Marketing Manager at CookieDev
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