Overview

Amazon CloudSearch

Stacks130

Followers152

Votes27

Algolia

Stacks1.4K

Followers1.1K

Votes699

Algolia vs Amazon CloudSearch: What are the differences?

Introduction:

Markdown is a lightweight markup language that is commonly used for formatting text on websites. In this task, I will format the provided content about the key differences between Algolia and Amazon CloudSearch as Markdown code that can be used on a website.

Indexing and Searching: Algolia focuses on delivering a real-time and interactive searching experience by providing instant search results as the user types. It offers advanced features like typo tolerance, faceted search, and synonyms out of the box. On the other hand, Amazon CloudSearch provides scalable search functionality with powerful indexing capabilities, making it suitable for large-scale applications that need efficient searching and filtering of structured data.
Data Integration: Algolia offers easy integration with various data sources such as databases, JSON files, and custom APIs. It provides connectors for popular platforms like Shopify, Magento, and WordPress, allowing seamless data synchronization. In contrast, Amazon CloudSearch is fully managed by AWS and can directly integrate with other AWS services like Amazon S3, Amazon DynamoDB, and Amazon RDS, enabling efficient data integration and synchronization with existing AWS infrastructure.
Pricing Model: Algolia offers a transparent pricing model based on the number of operations, records, and search traffic, making it suitable for applications with unpredictable usage patterns. It provides clear pricing tiers and offers a free trial for testing the service. Amazon CloudSearch, on the other hand, follows a pay-as-you-go pricing model based on instance and document batch size, along with additional charges for data transfer and search queries. It provides flexibility for scaling resources based on demand.
Infrastructure and Scalability: Algolia operates a globally distributed infrastructure with multiple data centers, ensuring low latency and high availability for search requests. It automatically handles scaling, replication, and failover to provide a reliable service. Amazon CloudSearch leverages the scalable and fault-tolerant infrastructure of AWS, allowing automatic scaling of resources based on workload demands. It supports multiple availability zones and provides robust data redundancy and recovery mechanisms.
Analytics and Monitoring: Algolia offers a comprehensive analytics dashboard that provides insights into search performance, user behavior, and conversion rates. It allows tracking and analyzing custom events, clickthrough rates, and conversion metrics for fine-tuning search relevance and effectiveness. Amazon CloudSearch integrates with AWS CloudWatch, enabling monitoring of search domain metrics, system health, and resource utilization. It provides configurable alarms and notifications for proactive monitoring and troubleshooting.
Customization and Extensibility: Algolia provides extensive customization options through a powerful set of APIs, allowing developers to fine-tune search relevance, create custom ranking rules, and implement personalized user experiences. It offers flexible query rules, synonyms management, and rich filtering capabilities. Amazon CloudSearch supports advanced search features like faceting and sorting, along with customizable relevance tuning. It provides integration with AWS Lambda, enabling extensibility through serverless functions for customizing search behavior.

In summary, Algolia and Amazon CloudSearch differ in aspects such as real-time search experience, data integration options, pricing model, infrastructure scalability, analytics capabilities, and customization/extensibility features.

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Advice on Amazon CloudSearch, Algolia

Akhil Kumar

software developer at arzooo

May 2, 2022

Needs advice

I want to design a search engine which can search with PAYMENT-ID, ORDER-ID, CUSTOMER-NAME, CUSTOMER-PHONE, STORE-NAME, STORE-NUMBER, RETAILER-NAME, RETAILER-NUMBER, RETAILER-ID, RETAILER-MARKETPLACE-ID.

All these details are stored in different tables like ORDERS, PAYMENTS, RETAILERS, STORES, CUSTOMERS, and INVOICES with relations. Right now we have only 10MBs of data with 20K records. So I need a scalable solution that can handle the search from all the tables mentioned and how can I make a dataset with so many tables with relations for search.

19.1k views19.1k

Comments

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

Phillip

Developer at Coach Align

Mar 18, 2021

Decided

The new pricing model Algolia introduced really sealed the deal for us on this one - much closer to pay-as-you-go. And didn't want to spend time learning more about hosting/optimizing Elasticsearch when that isn't our core business problem - would much rather pay others to solve that problem for us.

40.7k views40.7k

Comments

Detailed Comparison

Amazon CloudSearch	Algolia
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.	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.
Simple to Configure – You can make your data searchable using the AWS Management Console, API calls, or command line tools. Simply point to a sample set of data, and Amazon CloudSearch automatically proposes a list of index fields and a suggested configuration.;Automatic Scaling For Data & Traffic – Amazon CloudSearch scales up and down seamlessly as the amount of data or query volume changes.;Low Latency, High Throughput – Amazon CloudSearch always stores your index in RAM to ensure low latency and high throughput performance even at large scale. Amazon CloudSearch was created from the same A9 technology that powers search on Amazon.com.;Rich Search Features – Amazon CloudSearch indexes and searches both structured data and plain text. It includes most search features that developers have come to expect from a search engine, such as faceted search, free text search, Boolean search, customizable relevance ranking, query time rank expressions, field weighting, and sorting of results using any field. Amazon CloudSearch also provides near real-time indexing of document updates.;Secure – Amazon CloudSearch uses strong cryptographic methods to authenticate users and prevent unauthorized control of your domains. Amazon CloudSearch supports HTTPS and includes web service interfaces to configure firewall settings that control network access to your domain.	Database search;Multi-attributes;Search as you type;Analytics dashboard; Ranking; Mobile; Search in any language;Understand users mistakes;Smart Highlighting;Realtime indexing;Protect your indexes from misuse;Discover realtime faceting;Search objects by location
Statistics
Stacks 130	Stacks 1.4K
Followers 152	Followers 1.1K
Votes 27	Votes 699
Pros & Cons
Pros 12 Managed 7 Auto-Scaling 5 Compound Queries 3 Easy Setup	Pros 126 Ultra fast 95 Super easy to implement 73 Modern search engine 71 Excellent support 70 Easy setup, fast and relevant Cons 11 Expensive
Integrations
No integrations available	React Ruby Jekyll JavaScript React Native Vue.js WordPress Shopify Docusaurus VuePress

What are some alternatives to Amazon CloudSearch, Algolia?

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).

Solr

Solr is the popular, blazing fast open source enterprise search platform from the Apache Lucene project. Its major features include powerful full-text search, hit highlighting, faceted search, near real-time indexing, dynamic clustering, database integration, rich document (e.g., Word, PDF) handling, and geospatial search. Solr is highly reliable, scalable and fault tolerant, providing distributed indexing, replication and load-balanced querying, automated failover and recovery, centralized configuration and more. Solr powers the search and navigation features of many of the world's largest internet sites.

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.

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.

Manticore Search

It is a full-text search engine written in C++ and a fork of Sphinx Search. It's designed to be simple to use, light and fast, while allowing advanced full-text searching. Connectivity is provided via a MySQL compatible protocol or HTTP, making it easy to integrate.

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.

Swiftype

Swiftype is the easiest way to add great search to your website or mobile application.

MeiliSearch

It is a powerful, fast, open-source, easy to use, and deploy search engine. The search and indexation are fully customizable and handles features like typo-tolerance, filters, and synonyms.

Quickwit

It is the next-gen search & analytics engine built for logs. It is designed from the ground up to offer cost-efficiency and high reliability on large data sets. Its benefits are most apparent in multi-tenancy or multi-index settings.

Dejavu

dejaVu fits the unmet need of being a hackable data browser for Elasticsearch. Existing browsers were either built with a legacy UI and had a lacking user experience or used server side rendering (I am looking at you, Kibana).