Elasticsearch vs Jekyll

Overview

Elasticsearch

Stacks35.5K

Followers27.1K

Votes1.6K

Jekyll

Stacks2.0K

Followers1.4K

Votes230

GitHub Stars51.0K

Forks10.2K

Elasticsearch vs Jekyll: What are the differences?

Elasticsearch: 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); Jekyll: Blog-aware, static site generator in Ruby. Think of Jekyll as a file-based CMS, without all the complexity. Jekyll takes your content, renders Markdown and Liquid templates, and spits out a complete, static website ready to be served by Apache, Nginx or another web server. Jekyll is the engine behind GitHub Pages, which you can use to host sites right from your GitHub repositories.

Elasticsearch and Jekyll are primarily classified as "Search as a Service" and "Static Site Generators" tools respectively.

Some of the features offered by Elasticsearch are:

Distributed and Highly Available Search Engine.
Multi Tenant with Multi Types.
Various set of APIs including RESTful

On the other hand, Jekyll provides the following key features:

Simple - No more databases, comment moderation, or pesky updates to install—just your content.
Static - Markdown (or Textile), Liquid, HTML & CSS go in. Static sites come out ready for deployment.
Blog-aware - Permalinks, categories, pages, posts, and custom layouts are all first-class citizens here.

"Powerful api" is the primary reason why developers consider Elasticsearch over the competitors, whereas "Github pages integration" was stated as the key factor in picking Jekyll.

Elasticsearch and Jekyll are both open source tools. It seems that Elasticsearch with 41.9K GitHub stars and 14K forks on GitHub has more adoption than Jekyll with 38K GitHub stars and 8.28K GitHub forks.

According to the StackShare community, Elasticsearch has a broader approval, being mentioned in 1976 company stacks & 937 developers stacks; compared to Jekyll, which is listed in 110 company stacks and 123 developer stacks.

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Advice on Elasticsearch, Jekyll

Rana Usman

Chief Technology Officer at TechAvanza

Jun 4, 2020

Needs adviceon

Firebase

Elasticsearch

Algolia

Hey everybody! (1) I am developing an android application. I have data of around 3 million record (less than a TB). I want to save that data in the cloud. Which company provides the best cloud database services that would suit my scenario? It should be secured, long term useable, and provide better services. I decided to use Firebase Realtime database. Should I stick with Firebase or are there any other companies that provide a better service?

(2) I have the functionality of searching data in my app. Same data (less than a TB). Which search solution should I use in this case? I found Elasticsearch and Algolia search. It should be secure and fast. If any other company provides better services than these, please feel free to suggest them.

Thank you!

408k views408k

Comments

Manuel

Frontend Engineer at BI X

Jul 22, 2020

Decided

As a Frontend Developer I wanted something simple to generate static websites with technology I am familiar with. GatsbyJS was in the stack I am familiar with, does not need any other languages / package managers and allows quick content deployment in pure HTML or Markdown (what you prefer for a project). It also does not require you to understand a theming engine if you need a custom design.

178k views178k

Comments

Kazim

Founder & Developer at Devkind

May 13, 2020

Needs advice

Fastest and quickest way to do static HTML site which is extremely fast? Do you consider above tools or is there anything more quicker or better? This is just a one time one pager site for now, no backend required. I might have such projects in future, having something to get familiar with which can immediately come into action to develop would be great advise!

53.7k views53.7k

Comments

Detailed Comparison

Elasticsearch	Jekyll
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).	Think of Jekyll as a file-based CMS, without all the complexity. Jekyll takes your content, renders Markdown and Liquid templates, and spits out a complete, static website ready to be served by Apache, Nginx or another web server. Jekyll is the engine behind GitHub Pages, which you can use to host sites right from your GitHub repositories.
Distributed and Highly Available Search Engine;Multi Tenant with Multi Types;Various set of APIs including RESTful;Clients available in many languages including Java, Python, .NET, C#, Groovy, and more;Document oriented;Reliable, Asynchronous Write Behind for long term persistency;(Near) Real Time Search;Built on top of Apache Lucene;Per operation consistency;Inverted indices with finite state transducers for full-text querying;BKD trees for storing numeric and geo data;Column store for analytics;Compatible with Hadoop using the ES-Hadoop connector;Open Source under Apache 2 and Elastic License	Simple - No more databases, comment moderation, or pesky updates to install—just your content.;Static - Markdown (or Textile), Liquid, HTML & CSS go in. Static sites come out ready for deployment.;Blog-aware - Permalinks, categories, pages, posts, and custom layouts are all first-class citizens here.
Statistics
GitHub Stars -	GitHub Stars 51.0K
GitHub Forks -	GitHub Forks 10.2K
Stacks 35.5K	Stacks 2.0K
Followers 27.1K	Followers 1.4K
Votes 1.6K	Votes 230
Pros & Cons
Pros 329 Powerful api 315 Great search engine 231 Open source 214 Restful 200 Near real-time search Cons 7 Resource hungry 6 Diffecult to get started 5 Expensive 4 Hard to keep stable at large scale	Pros 74 Github pages integration 54 Open source 37 It's slick, customisable and hackerish 24 Easy to deploy 23 Straightforward cms for the hacker mindset Cons 4 Build time increases exponentially as site grows 2 Lack of developments lately 1 Og doesn't work with postings dynamically
Integrations
Kibana Beats Logstash	No integrations available

What are some alternatives to Elasticsearch, Jekyll?

Algolia

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.

Hugo

Hugo is a static site generator written in Go. It is optimized for speed, easy use and configurability. Hugo takes a directory with content and templates and renders them into a full html website. Hugo makes use of markdown files with front matter for meta data.

Gatsby

Gatsby lets you build blazing fast sites with your data, whatever the source. Liberate your sites from legacy CMSs and fly into the future.

Hexo

Hexo is a fast, simple and powerful blog framework. It parses your posts with Markdown or other render engine and generates static files with the beautiful theme. All of these just take seconds.

Middleman

Middleman is a command-line tool for creating static websites using all the shortcuts and tools of the modern web development environment.

Gridsome

Build websites using latest web tech tools that developers love - Vue.js, GraphQL and Webpack. Get hot-reloading and all the power of Node.js. Gridsome makes building websites fun again.

Typesense

It is an open source, typo tolerant search engine that delivers fast and relevant results out-of-the-box. has been built from scratch to offer a delightful, out-of-the-box search experience. From instant search to autosuggest, to faceted search, it has got you covered.

Pelican

Pelican is a static site generator that supports Markdown and reST syntax. Write your weblog entries directly with your editor of choice (vim!) in reStructuredText or Markdown.

Amazon CloudSearch

Amazon CloudSearch enables you to search large collections of data such as web pages, document files, forum posts, or product information. With a few clicks in the AWS Management Console, you can create a search domain, upload the data you want to make searchable to Amazon CloudSearch, and the search service automatically provisions the required technology resources and deploys a highly tuned search index.

Amazon Elasticsearch Service

Amazon Elasticsearch Service is a fully managed service that makes it easy for you to deploy, secure, and operate Elasticsearch at scale with zero down time.

Related Comparisons

Some of the features offered by Elasticsearch are:

Distributed and Highly Available Search Engine.
Multi Tenant with Multi Types.
Various set of APIs including RESTful

On the other hand, Jekyll provides the following key features:

Simple - No more databases, comment moderation, or pesky updates to install—just your content.
Static - Markdown (or Textile), Liquid, HTML & CSS go in. Static sites come out ready for deployment.
Blog-aware - Permalinks, categories, pages, posts, and custom layouts are all first-class citizens here.

"Powerful api" is the primary reason why developers consider Elasticsearch over the competitors, whereas "Github pages integration" was stated as the key factor in picking Jekyll.

Elasticsearch vs Jekyll