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Elasticsearch vs Algolia

Are you confused in choosing between a versatile search technology like Elasticsearch and a technology that simplifies search relevance configuration like Algolia? Here is all the information you require regarding Elasticsearch vs Algolia

The use of search can be advantageous for almost any app or website with more than a few pages. Whether  it's a global tech giant like YouTube or Facebook or small CRM, a forum in a niche corner of the internet, or, it's critical that users can find the information they need quickly and easily. Once a site reaches a certain size, it becomes almost mandatory to searching functionality and offload auto-suggest to a specialised tool that lifts the search experience out of the gutter and allows site-wide searches to be completed in milliseconds. Elasticsearch and Algolia are examples of such services.

Elasticsearch vs Algolia - Table Of Contents

How do site search solutions work?

Site search, in its broadest sense, is the functionality that allows website visitors to search specific keywords and/or criteria and receive relevant, ordered results from the site.

The functionality varies greatly - on some sites, you will only find a search bar where you can type keywords, whereas on others, faceted search will guide you step by step, in real time, based on all relevant attributes.

The basic concept is the same as on Google, but the underlying mechanics can vary greatly. The site search solution determines how individual site search engines interpret specific keywords and phrases, whether they can recognise typos, which product qualities are prioritised, how quickly results are returned, and how well facets and search filters work.

 working of site search solutions

To take changes into account and deliver results that are actually relevant, this index must be updated frequently.

Other search systems, like faceted search, do the procedure in real time, mostly based on all the many criteria offered for the various results. Of course, this requires more resources, but it is also considerably more user-friendly than routinely updating the search index.

Let's explore a couple site search solutions now that we've covered the fundamentals of site search.

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What is Elasticsearch?

Moreover, Elasticsearch has traditionally been self-hosted on a server under your control. More freedom and control over how the system is configured result from this, but it also makes the issue of permissions and security more obvious. If the system is not set up properly and with necessary care, your indexed data may be exposed to outside parties who may read and, in the worst circumstances, modify the data used by your site's search.

Elasticsearch

However, employing Elasticsearch shouldn't provide any security problems as long as the developer is competent. Additionally, there is the issue of somewhat increased technical maintenance and overhead, such as updating the server's software.

An answer for hosting and running Elasticsearch is offered by Amazon Web Services(AWS), a market-leading tool for everything web-related. This solution offers (in typical AWS style) a simplified interface to deal with your indexed data and settings. This speeds up the initial setup of the programme (in comparison to hosting your own instance) and helps get your supercharged search engine up and running quickly. If the developer has never used it before, it does need some research to utilise efficiently.

Amazon Web Services(AWS)

It's important to note that Elasticsearch now offers Elastic Cloud, a hosted SaaS option, which offers (as I would anticipate) a similar set of tools to Algolia.

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What is Algolia?

The hosting of the indexing system and the storage of all the data are handled by Algolia since it is a hosted SaaS (Software as a Service) solution. This results in less setup work for the system's engineers and a beautifully clear, user-friendly interface that makes it possible for you to see all of your data organised logically and modify any data points you need to.

Algolia

The solution also provides recent search metrics and daily usage graphs that are easy to understand. Algolia is often easier to use than Elasticsearch and allows more fine-grained control for the user to be able to customise the results that the searchers view through features like custom weighting for records and the option to define which fields are searchable.

In addition, Algolia provides a wide range of developer tools, including frameworks for integrating their service into your app regardless of what features it already has and comprehensive documentation for programmers to use in creating the finest system possible.

Pros and Cons of Elasticsearch vs Algolia

Pros and Cons of Elasticsearch

Pros:

  • It is typically regarded as being simple to use.
  • If the technical prerequisites are met, it is easily scalable and can handle Terabytes of data.
  • Complex keyword searches can be handled extremely effectively by it.
  • Because it gives its clients a full overview of user behaviour and search data, analytics is frequently cited as one of the best advantages.
  • Building various applications based on it is very simple and quick using REST-based APIs, an HTTP interface, and schema-free JSON documents for a range of use-cases (including, in addition to on-site search, processing genetic data, managing and analysing spatial information, modelling data behaviour etc.).

Cons:

  • Developers report a variety of drawbacks to using Elasticsearch in reviews, including occasional documentation gaps, troubleshooting difficulties, and a high learning curve.
  • It is not the best option for small businesses due to the cost.
  • Some developers have remarked that community support is more effective than that offered by the firm because support is not always proactive.
  • Even for seasoned developers, customising and switching between versions can be challenging.
Related Article: "Elasticsearch vs Solr"

Pros and Cons of Algolia

Pros:

  • It is quick and simple to implement.
  • It has top-notch support.
  • Modern and user-friendly technology underlies the system (for experts).
  • One of the most crucial search engine features is that it can deal with typos.
  • Additionally, it offers thorough analytics.

Cons:

  • Some developers claim that because the documentation is occasionally insufficient, it may be cumbersome and difficult to use.
  • The best option for small firms is typically not Algolia because it is one of the more expensive options.
  • It can be challenging to scale.
  • Algolia's customizable ranking is not perfect because it prioritises aspects rather than weighs each one separately.

Elasticsearch vs Algolia - Comparison

Although Elasticsearch and Algolia have many things in common, they also differ in significant ways. We shall go into more detail about their differences based on a few characteristics. The following distinctions are listed:

 ElasticsearchAlgolia
SpeedElasticsearch performs document searches well right out of the box, but it takes a significant amount of additional work to offer a user-friendly and feature-rich search.Algolia is made to cut down on latency. In a benchmarking exercise, Algolia outperformed Elasticsearch by 200x.
CustomersNumerous well-known companies use Elasticsearch, including Walmart, Uber, Netflix, Twilio, Adobe, Microsoft, Slack, and a number of other well-known companies.Coursera, Slack, Amazon, Amplitude, Lacoste, Intuit, BirchBox, Cafeyn, and numerous other companies are among the many clients of Algolia.
UI and dashboard visualizationElasticsearch lacks a GUI of its own. To interact with it, you must either install Kibana or add an extension to your browser. To engage with it, these plugins offer an interactive dashboard.Algolia provides APIs and front end widgets for a better user experience. When compared to other HMIs, Algolia features a dashboard with numerous filters, which improves it. You can set them up to display any data in a streamlined manner, including user behaviour and history.
HostingSelf-hosted on a server you own, Elasticsearch is a search engine. It can therefore configure the system exactly how you wish. However, it also has the issue of permission and security, which is a significant disadvantage. Nevertheless, Elasticsearch gives its consumers some flexibility.Algolia is a hosted SaaS option that takes care of both hosting the indexing engine and storing all of the data. Algolia is a hosted search engine that may be accessed via an API; it is not a database.
Release and costShay Banon released Elasticsearch in 2010. Since it is an open-source programme, there are no fees associated with using it. It is available for free download and installation from the company's website.Nicolas and Julien published Algolia in 2012. Along with a number of premium features, the Algolia community offers a 14-day free trial. The first 10 units of building searches are free.

FAQs Regarding the Difference Between Elasticsearch vs Algolia

1. Is Algolia better than Elasticsearch?

While both companies are search industry leaders, their strategies are vastly different. One significant distinction is that Algolia is a Cloud-native, purpose-built, managed service that boosts developer productivity by 5x when compared to Elastic's software, which can be hosted in the Cloud.

2. Is Algolia Search expensive?

They have a free plan that allows you to serve up to 10,000 search requests. Algolia Search is a $1.00/unit/month plan that includes analytics (20% off if paid annually).

3. Do I need to pay for Elasticsearch?

The charge for using our hosted Elasticsearch Service is a recurring fee if you are on a monthly plan. The fee is usually charged at the beginning of each month, but it can be charged at any time during the month. If a charge fails, we will attempt to charge your card again at a later time.

4. What is Algolia built on?

Algolia is powered by a search engine written from the ground up in C++ and hosted as an NGINX module within an NGINX server. The Algolia engine was originally designed for mobile devices as an offline, embeddable SDK before being transformed into an online API.

5. What is Elasticsearch built on?

Elasticsearch is a search and analytics engine based on Apache Lucene.

6. Is Algolia using Elasticsearch?

Facebook created Elasticsearch, a NoSQL database and search engine, in 2010. Algolia, on the other hand, is a search engine founded in 2012 by Nicolas and Julien. Elasticsearch is used to store unstructured data, and Algolia provides search APIs for performing searches.

7 .Is Algolia open source?

Algolia is heavily reliant on open source software and benefits from a variety of contributions made by individuals to the global developer community.

8. Is there a free version of Elasticsearch?

Yes, Elasticsearch's free and open features are available for use under either the SSPL or the Elastic License. The Elastic License includes additional free features, and paid subscriptions include access to support as well as advanced features like alerting and machine learning.

9. Is Elasticsearch SQL or NoSQL?

Elasticsearch is a cutting-edge search and analytics engine built on Apache Lucene. Elasticsearch is a NoSQL database that is completely open source and written in Java. That is, it stores data in an unstructured manner and cannot be queried using SQL.

10. Is Algolia a database?

Algolia is database-independent. It is compatible with any data source, including NoSQL databases. The indexing procedure is similar to that of any other database: fetch or  export the data from your database that you actually want to search in.

Conclusion

Depending on your demands, there are various reasons to select any of these two search engines from their distinct selling points. Having said that, they both offer features that can assist your site or app have a search that users will enjoy.

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Last updated: 18 Apr 2024
About Author

Kalla Saikumar is a technology expert and is currently working as a Marketing Analyst at MindMajix. Write articles on multiple platforms such as Tableau, PowerBi, Business Analysis, SQL Server, MySQL, Oracle, and other courses. And you can join him on LinkedIn and Twitter.

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