A Quick Comparison Between AWS ElasticSearch and CloudSearch

Posted By : Anirudh Bhardwaj | 27-Feb-2020

AWS ElasticSearch vs AWS CloudSearch

Amazon provides an exhaustive range of enterprise-grade cloud solutions to cross-industry businesses for enhanced security, transparency, and interoperability. Searching is a critical part of Amazon Web Services (AWS) that enables users to easily find the desired content on the internet. Providing an intuitive search interface is essential to augment customer satisfaction by delivering engaging user experiences. That being said, it is critical to select the right search tool for your application.

 

AWS cloud provides two advanced search tools that enable enterprises to strengthen their search engines for maximum user engagement and interactivity. These tools are:

 

  • Amazon ElasticSearch
  • Amazon CloudSearch

 

In this blog post, we are going to discuss the features, benefits, and feasible applications of these Amazon-exclusive search tools.

 

Also read Benefits Of Using AWS For DevOps

 

An Overview of Amazon ElasticSearch and CloudSearch

Both ElasticSearch and CloudSearch are cloud-based solutions from Amazon that enable users to create fast, scalable, and easy-to-use search solutions for their applications. The two solutions are quite similar except for a few notable variations in the form of features and capabilities. Let’s discuss the main points of differences between the two.

 

Access and Provisioning

Under Amazon Web Services (AWS), ElasticSearch is an independent search service run and maintained by elastic.co. It is an open-source cloud-based search solution that you may set up independently by downloading and extracting a group of files. Amazon ElasticSearch is a cost-effective search solution that is simple to install and easy to set up and use.

 

Amazon CloudSearch, on the other hand, is a fully managed cloud-based search solution that provides 360-degree search provisioning at minimal manual efforts. Using Apache Solr as the underlying text search engine, it renders full-fledged support for faceted search, full-text search, dynamic clustering, and real-time indexing. The AWS-based search solution also provides NoSQL features and facilitates database integration as well as productive document handling. 

 

Data Handling

Data processing is a significant feature of AWS-based search services. Both ElasticSearch and CloudSearch provide seamless data handling capabilities to users for their diverse applications. 

 

Amazon ElasticSearch incorporates dedicated plugins called ‘Rivers’ that are used to push data into a cluster for effective handling across devices. There are several different types of river plugins in ElasticSearch for carrying out different functions. Popular river plugins in AWS ElasticSearch are elasticsearch-river-mongodb, elasticsearch-river-jdbc, elasticsearch-river-couchdb, and more.    

 

In AWS CloudSearch, data or documents are converted into XML or JSON formats and then pushed in batches rather than clusters for indexing. For example, data may be pushed to S3 according to the defined path to achieve indexing. 

 

Upgrading and Customization

AWS ElasticSearch features are easy to upgrade. However, the upgrades are manual unlike Amazon CloudSearch. To upgrade an application, you simply need to replace the ‘lib’ folder of the existing search application with a new one.  

 

All major updates in AWS CloudSearch come directly from Amazon, eliminating the need for manual processing.  

 

Search and Indexing

AWS ElasticSearch incorporates search APIs to perform faceting and filtering of search data. The search APIs provide frictionless search features with several built-in libraries for indexing. 

 

CloudSearch provides a more simple approach for indexing through an easy configuration service. It enables users to upload their documents by creating a specific search domain including sub-services.

 

Licensing Requirements

AWS ElasticSearch is an open-source search solution that doesn’t have an up-front licensing requirement, and thus no additional costs for licensing. However, it requires an experienced team of developers (whether in-house or offshore) to handle complex features and custom functionalities.

 

CloudSearch imposes charges on an hourly basis, depending on the size of user searches. However, it doesn’t require dedicated developers as the operations are simplified and manable through a simple interface.

 

Security and Privacy

Amazon ElasticSearch offers a dedicated plugin to effectively handle user authentication, authorization, and permission allocation. The plugin called ‘Shield’ enables developers to carry out functions like encryption, auditing, IP filtering, and permissioned access control. However, shield is an add-on tool that must be purchased separately.  

 

Amazon CloudSearch provides IAM-based access control mechanism to grant users access to its features and resources. IAM stands for identity and access management and is used to assign different roles to users, on a permissioned level.

 

You may also be interested in reading Exploring the Benefits of Migrating Applications To AWS Cloud.

 

Conclusion

Both AWS ElasticSearch and CloudSearch provide fast, scalable, secure, reliable, and easy-to-use search solutions for a wide range of applications. While both services use advanced next-gen technologies to enhance search features, ElasticSearch is more suited for enterprise-level use cases. On the other hand, AWS CloudSearch is a fully managed platform that provides users access to custom features like plug-and-play startup, auto-patching, and automatic updates from Amazon. 

 

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About Author

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Anirudh Bhardwaj

Anirudh is a Content Strategist and Marketing Specialist who possess strong analytical skills and problem solving capabilities to tackle complex project tasks. Having considerable experience in the technology industry, he produces and proofreads insightful content on next-gen technologies like AI, blockchain, ERP, big data, IoT, and immersive AR/VR technologies. In addition to formulating content strategies for successful project execution, he has got ample experience in handling WordPress/PHP-based projects (delivering from scratch with UI/UX design, content, SEO, and quality assurance). Anirudh is proficient at using popular website tools like GTmetrix, Pagespeed Insights, ahrefs, GA3/GA4, Google Search Console, ChatGPT, Jira, Trello, Postman (API testing), and many more. Talking about the professional experience, he has worked on a range of projects including Wethio Blockchain, BlocEdu, NowCast, IT Savanna, Canine Concepts UK, and more.

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