Overview

Amazon CloudSearch

Stacks130

Followers152

Votes27

Amazon Elasticsearch Service

Stacks371

Followers288

Votes24

Amazon CloudSearch vs Amazon Elasticsearch Service: What are the differences?

Introduction:

When it comes to choosing between Amazon CloudSearch and Amazon Elasticsearch Service for search solutions in the cloud, there are several key differences to consider.

Data Structure and Querying Abilities: Amazon CloudSearch offers a more simplistic and limited data structure compared to Amazon Elasticsearch Service. CloudSearch is schema-less, which means less control over indexing and querying, while Elasticsearch allows for more complex data structures and querying capabilities using its powerful query language.
Scalability and Flexibility: Amazon Elasticsearch Service provides more scalability and flexibility in terms of cluster configuration, allowing users to customize hardware specifications, instance types, and storage options based on their specific requirements. CloudSearch has more restrictions in terms of cluster size and scaling options.
Integration with Other AWS Services: While both services integrate well with other AWS services, Amazon Elasticsearch Service has more extensive integrations with AWS services like Kinesis, CloudWatch, and IAM, allowing for seamless data pipelines and monitoring capabilities. CloudSearch also integrates with AWS services but may have limitations compared to Elasticsearch.
Pricing Model: Amazon CloudSearch has a simpler pricing model based on instance types and document batch uploads, making it easier to estimate costs for smaller workloads. In contrast, Amazon Elasticsearch Service pricing is more complex and based on cluster instance hours, storage, data transfer, and additional features like dedicated master nodes, which can be more cost-effective for larger workloads.
Management and Monitoring Tools: Amazon Elasticsearch Service provides more advanced management and monitoring tools, such as Kibana for data visualization, Elasticsearch API and console for cluster management, and integration with AWS CloudWatch for monitoring performance metrics. These tools make it easier to manage and monitor Elasticsearch clusters compared to CloudSearch.

In Summary, when choosing between Amazon CloudSearch and Amazon Elasticsearch Service, consider factors like data structure, scalability, integrations, pricing, and management tools to determine the best fit for your search solution in the cloud.

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Advice on Amazon CloudSearch, Amazon Elasticsearch Service

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

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

Ted

Computer Science

Dec 19, 2020

Review

I think elasticsearch should be a great fit for that use case. Using the AWS version will make your life easier. With such a small dataset you may also be able to use an in process library for searching and possibly remove the overhead of using a database. I don’t if it fits the bill, but you may also want to look into lucene.

I can tell you that Dynamo DB is definitely not a good fit for your use case. There is no fuzzy matching feature and you would need to have an index for each field you want to search or convert your data into a more searchable format for storing in Dynamo, which is something a full text search tool like elasticsearch is going to do for you.

42.9k views42.9k

Comments

Detailed Comparison

Amazon CloudSearch	Amazon Elasticsearch Service
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 is a fully managed service that makes it easy for you to deploy, secure, and operate Elasticsearch at scale with zero down time.
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.	-
Statistics
Stacks 130	Stacks 371
Followers 152	Followers 288
Votes 27	Votes 24
Pros & Cons
Pros 12 Managed 7 Auto-Scaling 5 Compound Queries 3 Easy Setup	Pros 10 Easy setup, monitoring and scaling 7 Kibana 7 Document-oriented
Integrations
No integrations available	Elasticsearch

What are some alternatives to Amazon CloudSearch, Amazon Elasticsearch Service?

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).

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.

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.

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.

Bonsai

Your customers expect fast, near-magical results from your search. Help them find what they’re looking for with Bonsai Elasticsearch. Our fully managed Elasticsearch solution makes it easy to create, manage, and test your app's search.

Azure Cognitive Search

It is the only cloud search service with built-in AI capabilities that enrich all types of information to easily identify and explore relevant content at scale. Formerly known as Azure Search, it uses the same integrated Microsoft natural language stack that Bing and Office have used for more than a decade and AI services across vision, language and speech. Spend more time innovating and less time maintaining a complex cloud search solution.