Amazon Cognito vs Elasticsearch

Overview

Elasticsearch

Stacks35.5K

Followers27.1K

Votes1.6K

Amazon Cognito

Stacks616

Followers917

Votes34

Amazon Cognito vs Elasticsearch: What are the differences?

Developers describe Amazon Cognito as "Securely manage and synchronize app data for your users across their mobile devices". You can create unique identities for your users through a number of public login providers (Amazon, Facebook, and Google) and also support unauthenticated guests. You can save app data locally on users’ devices allowing your applications to work even when the devices are offline. On the other hand, Elasticsearch is detailed as "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).

Amazon Cognito and Elasticsearch are primarily classified as "User Management and Authentication" and "Search as a Service" tools respectively.

Some of the features offered by Amazon Cognito are:

Manage Unique Identities
Work Offline
Store and Sync across Devices

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

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

"Backed by Amazon" is the primary reason why developers consider Amazon Cognito over the competitors, whereas "Powerful api" was stated as the key factor in picking Elasticsearch.

Elasticsearch is an open source tool with 42.4K GitHub stars and 14.2K GitHub forks. Here's a link to Elasticsearch's open source repository on GitHub.

Uber Technologies, Instacart, and Slack are some of the popular companies that use Elasticsearch, whereas Amazon Cognito is used by Sendhelper Pte Ltd, Strain Merchant, and ChromaDex. Elasticsearch has a broader approval, being mentioned in 2000 company stacks & 976 developers stacks; compared to Amazon Cognito, which is listed in 41 company stacks and 13 developer stacks.

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Advice on Elasticsearch, Amazon Cognito

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

Brent

CEO at DEFY Labs

Mar 7, 2020

Decided

I started our team on Amazon Cognito because I was a Solutions Architect at AWS and found it really easy to follow the tutorials and get a basic app up and running with it.

When our team started working with it, they very quickly became frustrated because of the poor documentation. After 4 days of trying to get all the basic passwordless auth working, our lead engineer made the decision to abandon it and try Auth0... and managed to get everything implemented in 4 hours.

The consensus was that Cognito just isn't mature enough or well-documented, and that the implementation does not cater for real world use cases the way that it should. I believe Amplify has made some of this simpler, but I would still recommend Auth0 as it's been bulletproof for us, and is a sensible price.

297k views297k

Comments

André

Nov 20, 2020

Needs adviceon

Elasticsearch

Amazon DynamoDB

Hi, community, I'm planning to build a web service that will perform a text search in a data set off less than 3k well-structured JSON objects containing config data. I'm expecting no more than 20 MB of data. The general traits I need for this search are:

Typo tolerant (fuzzy query), so it has to match the entries even though the query does not match 100% with a word on that JSON
Allow a strict match mode
Perform the search through all the JSON values (it can reach 6 nesting levels)
Ignore all Keys of the JSON; I'm interested only in the values.

The only thing I'm researching at the moment is Elasticsearch, and since the rest of the stack is on AWS the Amazon ElasticSearch is my favorite candidate so far. Although, the only knowledge I have on it was fetched from some articles and Q&A that I read here and there. Is ElasticSearch a good path for this project? I'm also considering Amazon DynamoDB (which I also don't know of), but it does not look to cover the requirements of fuzzy-search and ignore the JSON properties. Thank you in advance for your precious advice!

60.3k views60.3k

Comments

Detailed Comparison

Elasticsearch	Amazon Cognito
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).	You can create unique identities for your users through a number of public login providers (Amazon, Facebook, and Google) and also support unauthenticated guests. You can save app data locally on users’ devices allowing your applications to work even when the devices are offline.
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	Manage Unique Identities;Work Offline;Store and Sync across Devices;Seamless Guest Access;Safeguard AWS Credentials;Control Access to AWS Resources
Statistics
Stacks 35.5K	Stacks 616
Followers 27.1K	Followers 917
Votes 1.6K	Votes 34
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 14 Backed by Amazon 7 Manage Unique Identities 4 Work Offline 3 MFA 2 Store and Sync Cons 4 Massive Pain to get working 3 Documentation often out of date 2 Login-UI sparsely customizable (e.g. no translation) 1 Hard to find expiration times for tokens/codes 1 Different Language SDKs not compatible
Integrations
Kibana Beats Logstash	No integrations available

What are some alternatives to Elasticsearch, Amazon Cognito?

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.

Auth0

A set of unified APIs and tools that instantly enables Single Sign On and user management to all your applications.

Stormpath

Stormpath is an authentication and user management service that helps development teams quickly and securely build web and mobile applications and services.

Keycloak

It is an Open Source Identity and Access Management For Modern Applications and Services. It adds authentication to applications and secure services with minimum fuss. No need to deal with storing users or authenticating users. It's all available out of the box.

Devise

Devise is a flexible authentication solution for Rails based on Warden

Firebase Authentication

It provides backend services, easy-to-use SDKs, and ready-made UI libraries to authenticate users to your app. It supports authentication using passwords, phone numbers, popular federated identity providers like Google,

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 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.

WorkOS

Start selling to enterprise customers with just a few lines of code.

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Amazon Cognito vs Elasticsearch: What are the differences?

Amazon Cognito and Elasticsearch are primarily classified as "User Management and Authentication" and "Search as a Service" tools respectively.

Some of the features offered by Amazon Cognito are:

Manage Unique Identities
Work Offline
Store and Sync across Devices

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

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

"Backed by Amazon" is the primary reason why developers consider Amazon Cognito over the competitors, whereas "Powerful api" was stated as the key factor in picking Elasticsearch.

Elasticsearch is an open source tool with 42.4K GitHub stars and 14.2K GitHub forks. Here's a link to Elasticsearch's open source repository on GitHub.