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Address your search, observability, and security challenges with Elastic's leading vector database, built for generative AI, semantic search, and hundreds of open, pre-built integrations. Start a 7-day free trial and harness the power of your data, securely and at scale.
Overview
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Elastic's Search AI Platform combines world-class search with generative AI to address your search, observability, and security challenges.
Elasticsearch - the industry's most used vector database with an extensive catalog of GenAI integrations - gives you unified access to ML models, connectors, and frameworks through a simple API call. Manage data across sources with enterprise-grade security and build scalable, high-performance apps that keep pace with evolving business needs. Elasticsearch gives you a decade-long head start with a flexible Search AI toolkit and total provisioning flexibility-fully managed on serverless, in the cloud, or on your own infrastructure.
Elastic Observability resolves problems faster with open-source, AI-powered observability without limits, that is accurate, proactive and efficient. Get comprehensive visibility into your AWS and hybrid environment through 400+ integrations including Bedrock, CloudWatch, CloudTrail, EC2, Firehose, S3, and more. Achieve interoperability with an open and extensible, OpenTelemetry (OTel) native solution, with enterprise-grade support.
Elastic Security modernizes SecOps with AI-driven security analytics, the future of SIEM. Powered by Elastic's Search AI Platform, its unprecedented speed and scalability equips practitioners to analyze and act across the attack surface, raising team productivity and reducing risk. Elastic's groundbreaking AI and automation features solve real-world challenges. SOC leaders choose Elastic Security when they need an open and scalable solution ready to run on AWS.
Take advantage of Elastic Cloud Serverless - the fastest way to start and scale security, observability, and search solutions without managing infrastructure. Built on the industry-first Search AI Lake architecture, it combines vast storage, compute, low-latency querying, and advanced AI capabilities to deliver uncompromising speed and scale. Users can choose from Elastic Cloud Hosted and Elastic Cloud Serverless during deployment.
Ready to see for yourself? Sign into your AWS account, click on the "View Purchase Options" button at the top of this page, and start using a single deployment and three projects of Elastic Cloud for the first 7 days, free!
Highlights
- Search: Build innovative GenAI, RAG, and semantic search experiences with Elasticsearch, the leading vector database.
- Security: Modernize SecOps (SIEM, endpoint security, cyber security) with AI-driven security analytics powered by Elastic's Search AI Platform.
- Observability: Use open, extensible, full-stack observability with natively integrated OpenTelemetry for Application Performance Monitoring (APM) of logs, traces, and other metrics.
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Leverage AWS CloudFormation templates to reduce the time and resources required to configure, deploy, and launch your software.
Pricing
Free trial
Try this product free according to the free trial terms set by the vendor.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/unit |
|---|---|
Elastic Consumption Unit | $0.001 |
Dimensions summary
Elastic Consumption Units (ECUs) represent Elastic's unified pricing metric across both their Cloud Hosted and Serverless offerings on AWS Marketplace. For Cloud Hosted solutions, ECUs measure infrastructure resource consumption, while for Serverless offerings, ECUs quantify usage based on service-specific dimensions such as data ingestion, search operations, and security events. This flexible pricing model ensures customers pay only for their actual usage, whether they're using Elasticsearch, Observability, Security, or other Elastic services.
Top-of-mind questions for buyers like you
What is an Elastic Consumption Unit (ECU) and how is it calculated?
An ECU is Elastic's standardized billing metric that measures usage across their services. For Cloud Hosted deployments, ECUs are calculated based on infrastructure resources consumed, while for Serverless offerings, ECUs are determined by service-specific usage metrics like data ingestion volume, search operations, or security events processed.
How can I estimate my monthly costs for Elastic Cloud on AWS Marketplace?
Elastic provides a pricing calculator on their website where you can estimate costs based on your expected usage patterns. You can also monitor your actual ECU consumption through Elastic Cloud console's usage monitoring features, and the billing interface shows detailed breakdowns of usage by service and deployment.
Does Elastic Cloud on AWS Marketplace require any upfront commitment?
Elastic Cloud on AWS Marketplace follows a pay-as-you-go model with no upfront commitments required. However, customers can opt for annual commitments to receive volume discounts, and usage is billed monthly through your AWS account based on actual consumption of ECUs.
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
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Support
Vendor support
Visit Elastic Support (https://www.elastic.co/support ) for more information. If you are a customer, go to the Elastic Support Hub (http://support.elastic.co ) to raise a case.
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AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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By Elastic
By ChaosSearch, Inc.
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10
In Databases & Analytics Platforms
Top
10
In Generative AI, Log Analysis
Top
100
In Log Analysis, Analytic Platforms
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Vector Database Capabilities
Advanced vector database supporting generative AI, semantic search, and machine learning model integration through a unified API
Observability Platform
Comprehensive visibility across AWS and hybrid environments with over 400 integrations including CloudWatch, CloudTrail, EC2, and OpenTelemetry support
Security Analytics
AI-driven security analytics with advanced threat detection capabilities for SecOps, SIEM, and cross-surface attack analysis
Multi-Deployment Architecture
Flexible deployment options including serverless, cloud-hosted, and on-premise infrastructure with enterprise-grade security
Machine Learning Integration
Native support for machine learning models, connectors, and frameworks with seamless integration and scalable performance
Artificial Intelligence Analysis
Advanced AI agent that automates data analysis and accelerates root cause investigations
Telemetry Data Integration
Supports unified visibility across logs, metrics, and traces for cloud-native environments
Anomaly Detection
Real-time system anomaly detection to proactively prevent potential incidents
OpenTelemetry Compatibility
Flexible integration with OpenTelemetry standards for standardized observability pipelines
Multi-Architecture Support
Native compatibility with modern architectures including Kubernetes, serverless, and microservices environments
Data Indexing
Indexes Amazon S3 data without transformation, optimizing for data size and performance
Analytics Integration
Supports search, SQL, and machine learning workloads through open APIs with tools like Kibana, Elastic, Looker, and Tableau
Cloud Storage Transformation
Converts Amazon S3 into a hot analytical data lake with native indexing capabilities
Data Access Architecture
Enables direct data access without complex data pipelines, parsing, or schema changes
Scalability Mechanism
Provides infinite scale data analysis with no administrative overhead for re-indexing, sharding, or load balancing
Validated by AWS Marketplace
FedRAMP
GDPR
HIPAA
ISO/IEC 27001
PCI DSS
SOC 2 Type 2
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Standard contract
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Customer reviews
3.8
33 ratings
33 AWS reviews
|
220 external reviews
Star ratings include only reviews from verified AWS customers. External reviews can also include a star rating, but star ratings from external reviews are not averaged in with the AWS customer star ratings.
Harshul S.
Vraiment une expérience incroyable, facile à utiliser, facile à comprendre et facile à analyser.
Reviewed on Jul 11, 2025
Review provided by G2
Qu'aimez-vous le plus Ă propos de the product?
choisir le cloud est facile et cela fonctionne aussi bien avec des machines virtuelles qu'avec du matériel physique
Que n’aimez-vous pas à propos de the product?
il fonctionne avec Vm mais parfois ce n'est pas en temps réel, si vous définissez un événement, cela prend du temps
Quels sont les problèmes que the product résout, et en quoi cela vous est-il bénéfique?
un très bon outil comparé à d'autres comme qradar et d'autres outils sur le marché, facile à mettre en œuvre, facile à utiliser et à configurer, un outil vraiment efficace pour analyser les événements
PH Chiu
Log management capabilities impress but setup presents challenges
Reviewed on May 20, 2025
Review provided by PeerSpot
What is our primary use case?
The main use case for Elastic Search is mainly for log management.
What is most valuable?
I appreciate the indexing capabilities and the speed of indexing in their product, which demonstrates how quickly logs are collected and stored. The search capabilities are also valuable.
What needs improvement?
The architecture of Elastic Search could be improved as it is complicated for most general users to build up the environment and maintain the cluster.
Currently, I do not have suggestions for additional functions that could be added to the product.
For how long have I used the solution?
I have been working with Elastic Search for about two years.
What was my experience with deployment of the solution?
I usually use Elastic Search on-premises, which introduces complexity in deployment. Using the cloud version would reduce the complexity of setting up.
What do I think about the stability of the solution?
I would rate the stability for Elastic Search as eight out of ten.
What do I think about the scalability of the solution?
I would rate the scalability as eight.
How are customer service and support?
I would rate technical support from Elastic Search as three out of ten.
The main issue is a general sum of all factors. Being based in Hong Kong means I can only assess the service in my region and cannot speak for other regions based on my experience.
How would you rate customer service and support?
Negative
Which solution did I use previously and why did I switch?
I am currently working with multiple solutions including Elastic Search, Splunk, and Graylog .
How was the initial setup?
The initial setup for Elastic Search is complex.
What other advice do I have?
The real-time analytics capabilities depend on whether you use the paid version or open-source version.
I work with SME users of Elastic Search, though the solution can technically support enterprise customers.
I have not extensively used AI technology with Elastic Search.
I can recommend Elastic Search to other users.
The pricing for Elastic Search rates as four out of ten. Overall, I would rate Elastic Search as seven out of ten.
Which deployment model are you using for this solution?
On-premises
Himanshu Bhati
User optimizes data analysis with advanced search features and seeks expanded functionality
Reviewed on May 13, 2025
Review provided by PeerSpot
What is our primary use case?
I have been using it for a year. The main use cases involved implementing search functionality.
What is most valuable?
When discussing the features of Elastic Search , the full text search capabilities are particularly beneficial for handling large volumes of data.
The full text search capabilities in Elastic Search have proven to be extremely valuable for our operations.
Regarding AI integration, we have not yet implemented any AI-driven projects or initiatives using Elastic Search.
What needs improvement?
There are some features and functionality that could be enhanced in Elastic Search to improve its overall capabilities.
For how long have I used the solution?
I have been using Elastic Search for a year.
What do I think about the stability of the solution?
In terms of performance and stability, Elastic Search has proven to be a reliable solution.
What do I think about the scalability of the solution?
The environment includes multiple users utilizing Elastic Search across different locations.
Which solution did I use previously and why did I switch?
Before implementing Elastic Search, I had experience working with other search engines from different vendors.
How was the initial setup?
The implementation strategy involved specific steps during the setup process to ensure proper configuration.
What was our ROI?
The main benefits observed from using Elastic Search include improvements in operational efficiency, along with cost, time, and resource savings.
What other advice do I have?
I previously used Graylog .
I am currently working with Elastic Search as the primary solution.
My role is Senior DevOps engineer at UVIK Digital.
On a scale of 1 to 10, with 10 being the highest, I would rate Elastic Search as an 8 overall as a product and solution.
Aman K.
Un outil de big data NoSQL rapide, Ă©volutif et fiable
Reviewed on May 11, 2025
Review provided by G2
Qu'aimez-vous le plus Ă propos de the product?
C'est très rapide, facile à mettre en œuvre et évolutif, offrant une solution de bout en bout depuis l'ingestion de données en utilisant un grand nombre d'intégrations avec d'autres outils et plateformes, avec ses agents et ses protocoles d'ingestion de données et de communication pris en charge par l'open source, Elasticsearch comme base de données NoSQL et Kibana comme outil d'analyse, avec de nombreuses options pour les rapports et la visualisation des tableaux de bord, comme lens, tsvb, vega visualization et bien d'autres.
Que n’aimez-vous pas à propos de the product?
La migration à partir de bases de données traditionnelles qui contiennent des relations de plusieurs à plusieurs dans leurs schémas de tables est difficile à migrer vers Elasticsearch, car il existe d'autres astuces et techniques pour le faire, mais je pense que cela peut être amélioré.
Quels sont les problèmes que the product résout, et en quoi cela vous est-il bénéfique?
Il résout les problèmes de latence sur les réseaux, nous l'utilisons dans les solutions de cybersécurité, tout en travaillant avec des outils de big data car il est très rapide et offre des solutions de données de bout en bout avec diverses options disponibles, il propose des analyses de données ainsi que l'ingestion et des solutions de base de données rapides.
reviewer2702670
Efficient data storage and quick searching boost productivity
Reviewed on May 06, 2025
Review from a verified AWS customer
What is our primary use case?
Our primary use case was primarily for data storage and quick searching. We focused on getting objects from the database and filtering them efficiently. This involved getting and searching through objects.
How has it helped my organization?
Our productivity was consistently maintained while using this database. Its consistent performance allowed us to maintain steady productivity levels.
What is most valuable?
The most valuable feature of Elasticsearch was the quick search capability, allowing us to search by any criteria needed. The searches were executed very quickly, which made the process reliable. Additionally, full-text queries were integral to our usage. Our productivity was consistently maintained with this database. Its consistent performance allowed us to maintain steady productivity levels.
What needs improvement?
It would be useful if a feature for renaming indices could be added without affecting the performance of other features. However, overall, the consistency and stability of Elasticsearch are already commendable, and they should keep up the good work.
For how long have I used the solution?
I have been using Elasticsearch for two and a half years while at this company.
What do I think about the stability of the solution?
The stability of Elasticsearch was very high, and I would rate it a ten. It was consistent and reliable in our usage.
What do I think about the scalability of the solution?
Elasticsearch was decently scalable, matching our data growth. I would rate its scalability a ten.
How was the initial setup?
I was not involved in the initial setup. However, the setup process for smaller projects was straightforward.
What about the implementation team?
One person from our DevOps team was responsible for the maintenance of Elasticsearch.
What's my experience with pricing, setup cost, and licensing?
We used the open-source version of Elasticsearch, which was free.
What other advice do I have?
If a feature for renaming indices could be added without affecting the performance of all other features, it would be nice to have. Overall, I rate Elasticsearch a ten out of ten.
Which deployment model are you using for this solution?
Public Cloud