Elasticsearch vs. CloudSearch: AWS Cloud

Today, more than 100 billion searches are conducted every month on the Google search engine alone. Search engine users conduct searches for several reasons including the foundational conversion of information into action. An action could be a decision to purchase, consume information for decision-making, or seek a better understanding of an issue or topic among others. Search engines make information available at our fingertips right whenever we need it.

In this era of big data, search solutions are useful not only for popular search engines like Google, Yahoo, and Bing but also for enterprises for monitoring and managing the growing volumes of data in their databases to enhance operational efficiency. The enterprise search industry has grown remarkably and is expected to be worth $8.90 billion by 2024.

Enterprise search solutions are important for several reasons:

  • They provide fast and easy access to crucial data from multiple databases in one search query.
  • Enterprise search provides the flexibility required to search data in a wide range of formats.
  • Enhance data security by limiting data access only to authorized users.
  • Enterprise search solutions hosted on the cloud significantly lower installation and system maintenance costs while still providing optimum operational efficiency
  • The use of site search tools enhances the customer experience by allowing them to search the system fast and conveniently, ultimately leading to more conversions and increased sales.

Cloud search services are the go-to search solutions for many enterprises as they are fully managed and scale easily. However, deploying, upgrading, and managing search solutions requires specific skills and in many cases demands that a professional possesses a cloud certification. Elasticsearch clusters are particularly complex, requiring technical skills to deploy and manage.

AWS Elasticsearch

AWS Elasticsearch is a distributed NoSQL database service that stores unstructured data in document format. It is a managed search and analytics service that allows users to deploy and scale Elasticsearch on the AWS cloud. AWS Elasticsearch is compatible with your existing code and applications thanks to its RESTful API. It features integrated support for Kibana, an open-source user interface used for visualizing and analyzing Elasticsearch data, as well as Logstash, a lightweight data processing pipeline that collects and transforms data for loading into your clusters. It supports multiple languages ​​including Python, Java, JavaScript, PHP, Ruby, and more, and is also integrable with a number of open-source plugins to increase its capabilities.

Setting up, configuring, and scaling AWS Elasticsearch takes a matter of minutes from the AWS management console. This service will automatically provision and launch the resources needed to run your clusters while also identifying and replacing failed nodes within the clusters for streamlined operations. AWS Elasticsearch is enabled with AWS IAM (AWS identity access management) for controlling access to your data environment. AWS Elasticsearch is also equipped with other features including Snapshot for data backup, Amazon CloudWatch for domain monitoring, and AWS CloudTrail for risk auditing.

AWS Elasticsearch is used for a range of applications, including log analytics, real-time application monitoring, and click-stream analytics.

AWS CloudSearch

AWS CloudSearch is one of the fully managed search services in AWS cloud services offerings for websites and applications. AWS CloudSearch is designed to scale on-demand to ensure efficient operations and optimum availability of service during high volume data and complex search requests. It enables enterprises to navigate huge volumes of databases containing document files, emails, clickstream logs, social network posts, transactional data from systems, customer data in CRM systems, network and server log files, data from sensors and IoT devices, and more.

Being a cloud service, AWS CloudSearch is relatively fast, easy, and cost-effective to set up and manage to allow users to create a search domain, load data, and provide resources for a custom search index with a few clicks. It allows users to quickly incorporate additional search capabilities and scale search services or modify search parameters to meet data and traffic demands for their sites and applications. Billing is done on a pay-as-you-go schedule which makes it cost-effective as users only pay for the service they have consumed.

AWS CloudSearch supports 34 programming languages ​​and features highlighting, autocomplete, geospatial, and other innovative search features that improve the search experience.

Elasticsearch vs. CloudSearch

Both AWS Elasticsearch and AWS CloudSearch offer immense advantages over self-managed data search engines and analytics services. They are set up and configured easily, they are both easily scalable, and they automatically provide the resources you require to customize your search index.

However, these two search services are different in many ways as we have highlighted in the table below.

AWS Elasticsearch

AWS CloudSearch


Is an open-source distributed search engine that is configured by the user using RESTful APIs. The user manages patches and updates automatically using third-party plugins or manually. Data is stored in spatial database management systems.

Is a hosted search engine whose updates and patches are fully managed by AWS on behalf of the user to ensure high availability of service. In CloudSearch, data is stored in the cloud.



Commercial licensing

Data import and export

Imports massive volumes of data using the river function as well as with third-party integrations and importers.

Imports high volume data in JSON and XML formats in batches or from AWS S3.

Data backup and restore

Uses the Snapshot function to take daily automatic or manual snapshots of primary index shards in the domain for backup and restoration.

Automatically manages all backup and restore processes without the involvement of users.

Cluster management

Users use either the web dashboard or CLI tools to configure clusters, nodes, and instances types. Indexes are organized into shards for easy replacement of lost data in failed nodes.

Cluster management is fully managed and automated.


Scaling of clusters is done by the user through the management console, CLI, or SDKs.

Automaticly scales up and down depending on data and query volumes.


Elasticsearch APIs allow users to configure replicas for their clusters to enable the high availability of data. Instances are spread between two availability zones.

Out-of-the-box availability and failover capabilities.

Search and indexing capabilities

Feature several libraries and clients to facilitate efficient searching and indexing. The maximum allowed file size is 1MB and 5MB or 1000 documents per batch for bulk operation.

The maximum allowed file size is 2GB while the maximum allowed bulk operation is 100MB which is higher.

Integration capabilities

Comes integrated with tools like Kibana, Snapshot, and Logstash.

CloudSearch is in itself an API but integrates with Hadoop.


Determined by monthly consumption, data volumes transferred instance type, storage type, and size.

Determined by instance size, batch uploads, and re-indexing requests.

Ideal for

Is ideal for situations that require the flexibility of integration with third-party plugins making it best for data analytics.

Fully managed AWS comes completely configured for high availability and efficiency. This makes it great for end-user document search.


Amazon offers a range of cloud solutions for enterprises, with Elasticsearch and CloudSearch being two of its most used search solutions. Searching helps users to find the information that they are looking for fast and easily. Enterprises are on the lookout for the right search solutions for their applications. The right solution enhances user experience, streamlines operations, and enhances productivity.


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