Amazon Elasticsearch Service vs Elastic Cloud

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Amazon Elasticsearch Service

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Elastic Cloud

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Amazon Elasticsearch Service vs Elastic Cloud: What are the differences?

Introduction This markdown code provides a comparison between Amazon Elasticsearch Service and Elastic Cloud, highlighting key differences between the two.

  1. Pricing Model: Amazon Elasticsearch Service offers Pay-As-You-Go pricing, allowing users to pay only for the resources they consume, with no upfront costs or minimum fees. On the other hand, Elastic Cloud offers subscription-based pricing, with various tiers based on the desired features and resources.

  2. Deployment and Management: Amazon Elasticsearch Service is fully managed by Amazon Web Services (AWS), taking care of deployment, patching, scaling, and monitoring, which relieves users from the operational burden. Elastic Cloud, on the other hand, offers a managed service as well but supports deployment on various cloud providers including AWS, Microsoft Azure, and Google Cloud Platform.

  3. Advanced Features: Amazon Elasticsearch Service supports additional features such as integration with AWS services like Kinesis Data Firehose, CloudWatch, and Identity and Access Management (IAM). It also provides the ability to deploy Elasticsearch clusters in multiple Availability Zones for high availability. Elastic Cloud, on the other hand, offers advanced features including machine learning, anomaly detection, and security features like role-based access control (RBAC), encryption at rest, and SSL/TLS encryption.

  4. Scalability: Both Amazon Elasticsearch Service and Elastic Cloud offer scalable solutions. However, Amazon Elasticsearch Service allows users to easily provision and scale resources on-demand, automatically handling the underlying infrastructure to ensure high availability and performance. Elastic Cloud also provides scalability but requires manual setup and configuration for resource scaling.

  5. Integration with Other Tools: Amazon Elasticsearch Service seamlessly integrates with various AWS services like Amazon S3, Amazon CloudWatch, and AWS Identity and Access Management. This integration allows users to easily ingest and analyze data from different sources. Elastic Cloud, on the other hand, offers integrations with a wide range of third-party tools and services, allowing users to extend the functionality and capabilities of their Elasticsearch clusters.

  6. Support and Documentation: Amazon Elasticsearch Service provides support and documentation through the AWS Support Center, offering different levels of support plans based on user requirements. Elastic Cloud offers support through the Elastic Support Portal, providing various support plans including basic, standard, and enterprise levels. Both platforms also have extensive documentation available for users to refer to.

In Summary, Amazon Elasticsearch Service and Elastic Cloud differ in their pricing models, deployment and management approaches, advanced features, scalability options, integration capabilities, and support and documentation offerings.

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Pros of Amazon Elasticsearch Service
Pros of Elastic Cloud
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    Easy setup, monitoring and scaling
  • 7
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    What is 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.

    What is Elastic Cloud?

    A growing family of Elastic SaaS offerings that make it easy to deploy, operate, and scale Elastic products and solutions in the cloud. From an easy-to-use hosted and managed Elasticsearch experience to powerful, out-of-the-box search solutions.

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    What are some alternatives to Amazon Elasticsearch Service and Elastic Cloud?
    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).
    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.
    ELK
    It is the acronym for three open source projects: Elasticsearch, Logstash, and Kibana. Elasticsearch is a search and analytics engine. Logstash is a server‑side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a "stash" like Elasticsearch. Kibana lets users visualize data with charts and graphs in Elasticsearch.
    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.
    Swiftype
    Swiftype is the easiest way to add great search to your website or mobile application.
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