Choosing a Search Engine For Your CMS: Algolia vs Elasticsearch
Amanda Lee loves writing, photography, and coffee.
Search functionality can play an important role in any digital user experience, regardless of the type of website you’re running. For an enterprise website, it can help sort through thousands of product pages, blog articles or training guides. And it can personalize the overall experience. For an eCommerce store, it can help customers find the exact product they’re looking for in milliseconds rather than browsing an entire catalog. For a CMS, it’s also important for the content authoring experience.
Given how valuable search capabilities are to a CMS, selecting the right option is essential. Two of the most popular options are Algolia and Elasticsearch, each with pros and cons. So which one is the right choice for your CMS? Let’s assess the options and see how they work with a composable and headless CMS such as CrafterCMS.
What Is Algolia?
Algolia offers a cutting-edge API platform that provides search and discovery for businesses, leveraging AI to optimize relevance tuning. The solution ensures fast access to the right content or product on your website or app, providing a seamless and intuitive user experience.
Algolia Search is a highly efficient, fully hosted API that ensures quick content delivery to users. The platform empowers developers to tailor the relevance of their user experience and provides valuable insights into user interactions. Meanwhile, Algolia Recommend is a robust API that enables the integration of unique product recommendations into any eCommerce digital experience.
Algolia is typically easy to integrate with other API-first tools and offers a ready-to-use solution out of the box. Many eCommerce stores, particularly, can leverage Algolia without worrying about using their own infrastructure.
Advantages of Algolia
- Speed: Algolia’s search algorithms are designed for speed and can return relevant results in milliseconds.
- Smooth Integrations: Algolia provides API clients for several languages, making it easy to integrate into your website or application.
- Customizable Relevance: You can fine-tune the ranking of search results and get more control over what users see first.
- Scalability: Algolia can handle large amounts of data and traffic, so you can scale your search as your business grows.
- Analytics: Algolia provides detailed analytics and search statistics, so you can measure the success of your search and make data-driven improvements.
- User-friendly Dashboard: Algolia offers a user-friendly dashboard for managing your search data, customizing search behavior, and monitoring performance.
Cons of Using Algolia
- Cost: Algolia’s pricing model is based on the number of searches and data transfers, which can become expensive for high-traffic sites.
- Complexity: Advanced features can be difficult to set up and configure, especially for users with limited technical expertise.
- Dependence on API: Algolia relies on its API for search functionality, so if the hosted API goes down or becomes unavailable, your search will be impacted.
What Is ElasticSearch?
Elasticsearch is an open-source search and analytics engine that handles all types of data - from textual to geospatial, structured to unstructured. Elasticsearch is built on the Apache Lucene platform, and was first released by Elasticsearch N.V. (now Elastic) in 2010. Since then, Elasticsearch has been hailed for its ease of use through simple REST APIs, robust distributed architecture, lightning speed, and scalability.
As the central component of the Elastic Stack - a comprehensive suite of free and open tools for data management and analysis - Elasticsearch streamlines the entire data pipeline, from ingestion to visualization. This complete solution is often called the ELK Stack and includes Elasticsearch, Logstash, and Kibana.
Since Elasticsearch is open source, this means more control and versatility in search data processing. Unlike other solutions, this also means you can avoid vendor lock-in. It can also be a more economical choice, particularly if you have extensive data or complex search needs.
Elasticsearch is a go-to solution for efficiently storing, accessing, and analyzing massive amounts of diverse data in real time.
- Open-source: Elasticsearch is (mostly) open-source software, so it is freely available and can be modified to meet specific needs. Note, we say “mostly” because Elastic recently changed their license model to a more restrictive one, not allowing users to host Elastic as a service. For a true open source alternative to Elastic, Opensearch is the AWS-sponsored fork of Elasticsearch that remains under the open source Apache 2.0 license.
- Scalability: Elasticsearch is designed to scale horizontally, so you can add more nodes to handle increased traffic and data.
Robust Features: Elasticsearch provides a wide range of search and analytics features, including full-text search, geospatial search, and real-time analytics.
- Large Community: Elasticsearch has a large and active community of developers who contribute to the software and provide support to users.
- Ease of Integration: Elasticsearch integrates well with other tools and technologies, including the rest of the Elastic Stack (e.g., Kibana, Logstash, Beats), as well as third-party tools like Apache Hadoop.
- High Performance: Elasticsearch is optimized for high performance and can handle large amounts of data and traffic.
- Flexibility: Elasticsearch provides a flexible data model, allowing you to store, search, and analyze structured and unstructured data. You also have the option of choosing to host it yourself, use a managed service provider, or use Elastic’s SaaS option.
- Learning Curve: Elasticsearch is flexible and feature-rich, but it can be difficult to learn and use, especially for users with limited technical expertise.
- Complex Configuration: Elasticsearch has many configuration options, which can be overwhelming and lead to poor performance if not set up correctly.
- Limited Security Features: Elasticsearch offers simple security features, such as authentication and SSL encryption, but it does not have a comprehensive security solution built-in.
Choosing Between Algolia and Elasticsearch
The debate between Algolia and Elasticsearch essentially depends on whether you want to use an open source tool or a SaaS-based solution, and whether the advantages of Algolia justify the additional cost. Both allow you to integrate the search engine and search functionality into the rest of your technology stack.
However, using Algolia requires you to bear the additional licensing costs of another platform on top of your existing content management system. But what if a headless CMS already has robust search functionality built-in with Elasticsearch? Then deciding between the two becomes a choice rather than a requirement.
Search Functionality in CrafterCMS
CrafterCMS is a headless CMS for the enterprise and offers world-class search built-in. Elasticsearch comes bundled into both Crafter Studio (content authoring platform and app) and Crafter Engine (API-first headless content delivery delivery platform), so content authors get a powerful search capability out of the box. Meanwhile, developers building sites and apps get access to a rich search API for building personalized, engaging end user digital experiences (websites, mobile apps, e-commerce, OTT video, etc.).
If developers prefer another search engine for the end user experiences, such as Algolia, they have that option as well. As a services-oriented, API-first and composable platform, CrafterCMS provides you the flexibility to choose the “best of stack” search engine that works best for your use case(s), with the added convenience of Elasticsearch already available out of the box. With other headless CMS options, you need to integrate a separate search engine, whether Elasticsearch or Algolia or another, but CrafterCMS gives you more freedom to choose.
In addition, as CrafterCMS stores content as files in it's Git-based repository (for content authoring) and in-memory (for content delivery), search is much faster when compared to database-oriented CMSs. Searching structured content stored in external databases with any search engine is fundamentally slower and less efficient than CrafterCMS’s superior architectural approach.
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