Sold by: Teradata
Deployed on AWS
Teradata VantageCloud is the complete enterprise analytics delivered on AWS. Unify structured, semi-structured, and unstructured data with integrated analytics and AI to activate trusted knowledge at scale.
4.3
Overview
Teradata VantageCloud is the complete enterprise analytics and AI platform, delivered on AWS. Part of the Teradata Autonomous Knowledge Platform, it unifies structured, semi-structured, and unstructured data with integrated analytics and AI capabilities, enabling organizations to activate trusted knowledge at scale.
The Teradata Database includes advanced in-database analytics as standard: machine learning, geospatial, time series, graph, text, and path analytics are all built in. Teams can build, train, and score models directly where the data lives, using SQL, Python, R, and leading AI/ML frameworks, without moving data to external compute environments.
The Connected Data Foundation provides native support for Open Table Formats including Apache Iceberg and Delta Lake, enabling interoperability with lakehouse architectures on shared object storage. Teradata QueryGrid extends connectivity across Teradata and third-party systems, allowing federated queries with optimizer-driven pushdown across cloud and on-premises environments without data movement or duplication.
Teradata VantageCloud is available with Tcore-based pricing and packaging; we recommend speaking to a Teradata representative before purchasing to identify the best configuration for your workloads.
Your subscription includes Teradata Premier Cloud Support and rights to use Teradata Data Stream Controller; Teradata Query Service; Teradata Server Management; and Teradata Viewpoint. See product documentation on the Teradata website for details.
Get started now by clicking on "Continue to Subscribe".
NOTE: This AMI uses a 550 GB EBS volume for root disk; Teradata QueryGrid Connector is licensed separately.
Highlights
- Powerful software tier boasting exceptional economics via a system concurrency limit of 15. Operationalize insights and enable descriptive, diagnostic, predictive, and prescription analytics.
- Vector Store (SQL Interface) enables organizations to store, manage, and query vector embeddings directly in Teradata VantageCloud, accelerating RAG, semantic search, and generative AI use cases without moving data outside the platform.
- Connected Data Foundation: Native support for Apache Iceberg and Delta Lake Open Table Formats enables seamless interoperability with lakehouse architectures, while Teradata QueryGrid provides federated query access across Teradata and third-party systems without data movement.
Details
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Delivery method
Delivery option
Teradata Vantage local/EBS storage - existing VPC
Latest version
Operating system
OtherLinux SLES 15 SP7
Deployed on AWS
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Buyer guide
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Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
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. Alternatively, you can pay upfront for a contract, which typically covers your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/hour |
|---|---|
d2.xlarge | $0.393 |
m5.4xlarge | $2.422 |
m5.12xlarge | $6.144 |
m5.24xlarge | $12.297 |
t3.medium | $0.16 |
r5.12xlarge | $6.14 |
r5.16xlarge | $8.41 |
r5.24xlarge | $12.29 |
r5.4xlarge | $2.42 |
r5.8xlarge | $4.20 |
Dimensions summary
You pay by the hour based on the AWS EC2 instance type you run. This is a do-it-yourself deployment, so pricing scales with the compute size you choose. The options span several instance families. General-purpose (m5) sizes handle balanced workloads. Memory-optimized (r5 and r6i) sizes suit memory-heavy analytics. A dense-storage (d2) option and a small burstable (t3) option round out the range. Within each family, larger instance sizes carry higher hourly rates. You select the instance that fits your workload, and billing tracks the hours you run it.
Top-of-mind questions for buyers
Each hour maps to one running EC2 instance of the size you pick. For example, an r5.24xlarge hour is one r5.24xlarge instance running for one hour. Larger sizes offer more vCPUs and memory, so their hourly rate is higher. You pay per instance-hour of running time.
The software charge meters running hours only. A stopped instance does not accrue the hourly software fee. Underlying AWS storage or other AWS resources may still bill separately while the instance is stopped. Charges resume when you start the instance again.
Pick based on your workload profile. General-purpose m5 sizes fit balanced compute. Memory-optimized r5 and r6i sizes fit memory-heavy analytics. The d2 dense-storage option fits storage-heavy work. The t3.medium burstable option fits light or intermittent use. Each meters the same hourly way; only the rate differs.
www.teradata.com
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Vendor refund policy
We do not provide refunds but you may cancel at any time.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Teradata Vantage local/EBS storage - existing VPC
Teradata Vantage multi-node system with local storage SSD/HDD or EBS as data storage and deployed in an existing VPC.
CloudFormation Template (CFT)
AWS CloudFormation templates are JSON or YAML-formatted text files that simplify provisioning and management on AWS. The templates describe the service or application architecture you want to deploy, and AWS CloudFormation uses those templates to provision and configure the required services (such as Amazon EC2 instances or Amazon RDS DB instances). The deployed application and associated resources are called a "stack."
Version release notes
Teradata Cloud DIY 3.4 Release (AWS) Teradata Cloud DIY 3.4 introduces new capabilities that make it easier to work with modern lakehouse architectures, accelerate AI initiatives, and expand infrastructure flexibility across AWS.
What's New Vector Store (SQL Interface)
- Build semantic search, RAG, and AI applications using vectors stored and managed through SQL.
- Keep enterprise data governed and closer to where AI workloads run.
Open Table Format (OTF) Enhancements
- Native support for Unity Catalog RBAC.
- Direct access to Microsoft Fabric OneLake data.
- Faster Delta table reads.
- High-performance Apache Iceberg writes.
- Support for Iceberg 3.0 deletion vectors.
Platform Enhancements
- New VM options for improved OTF performance and deployment flexibility.
- AWS support for Graviton (ARM-based) infrastructure for improved price-performance (Teradata Cloud DIY Sovereign).
Pricing Update
- ARM-based VM families use a different pricing metric called Unit Pricing instead of TCore Pricing.
IMPORTANT NOTICE Analytics Database 17.20 will reach End of Life (EoL) on June 30, 2027. Until then, only critical bug fixes will be delivered through maintenance releases. Customers using version 17.20 are strongly encouraged to upgrade to a 20.xx release. If an immediate upgrade is not possible, customers must:
- Have a documented upgrade plan reviewed with the Teradata Global Change Control team, or
- Obtain an approved exception.
For guidance, contact Teradata Support or your Teradata Account Team. Starting in Q3 2026, Version 17.20 will not be be available for new deployments via the Marketplace. Customers planning new deployments should select a newer supported version (20.xx).
Additional details
Usage instructions
This product is designed to work with other Teradata software products.
- Use CloudFormation template to launch a multi-node Teradata Vantage system.
- System will be up and running after stack launch is complete.
- Verify system state: a) ssh into the one of the instances: ssh -i <private key file> ec2-user@<instance DNS name or IP address> b) Validate the system is up and running: sudo psh pdestate -a The output of the command will be similar to: all N nodes: PDE state is RUN/STARTED. DBS state is 5: Logons are enabled - The system is quiescent
For more information, visit our Product Documentation listed at https://www.teradata.com/Products/Cloud/Do-it-yourself/AWS .
Resources
Support
Vendor support
Teradata Premier Cloud Support is bundled with your paid software subscription. It provides 24x7 incident creation for problem resolutions, coverage and response times by customer-defined severity levels, and entitlement to software updates. Note: For customers who want to buy Teradata Ecosystem applications such as Data Stream Controller, Query Service, Query Grid Manager and Server Management, please contact Teradata Account team and refer to https://www.teradata.com/Cloud/AWS/Do-it-Yourself
AWS infrastructure support
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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AI generated from product descriptions
In-Database Analytics Capabilities
Advanced in-database analytics including machine learning, geospatial, time series, graph, text, and path analytics built into the database engine
Multi-Format Data Support
Native support for structured, semi-structured, and unstructured data with integrated analytics and AI capabilities
Vector Embedding Management
Vector Store with SQL Interface for storing, managing, and querying vector embeddings directly in the platform to support RAG, semantic search, and generative AI use cases
Open Table Format Interoperability
Native support for Apache Iceberg and Delta Lake Open Table Formats enabling seamless interoperability with lakehouse architectures on shared object storage
Federated Query Execution
Teradata QueryGrid providing federated query access across Teradata and third-party systems with optimizer-driven pushdown across cloud and on-premises environments without data movement
Lakehouse Architecture
Unified data foundation built on lakehouse architecture providing open, unified foundation for data and governance with support for open standards and formats
Data Intelligence Engine
Powered by Data Intelligence Engine that enables organization-wide access to data and insights across all users and roles
Multi-Workload Unification
Consolidates data engineering, analytics, business intelligence, data science and machine learning workloads on a single common platform
Open Source Foundation
Built on open source data projects and open standards to maximize flexibility and interoperability across data ecosystem
Collaborative Capabilities
Native collaboration features enabling unified data teams to collaborate across entire data and AI workflow
Auto-scaling Capability
Intelligently autoscales workloads up and down across hybrid and public cloud environments for optimized cloud infrastructure utilization.
Multi-function Analytics Platform
Provides integrated data warehouse, machine learning, and custom analytics services with standardized user experience for ingesting, transforming, querying, optimizing, and making predictions from data.
Unified Security and Governance Framework
Implements Shared Data Experience (SDX) technology that sets security and governance policies once and applies them consistently across all data and workloads regardless of infrastructure.
Cross-infrastructure Policy Portability
Maintains security and governance policies with data as it moves across multiple public clouds, private cloud, and hybrid cloud environments.
Centralized Data Management and Discovery
Provides unified metadata management enabling efficient data curation, discovery, and sharing while eliminating data silos and redundant data copies.
Standard contract
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Customer reviews
Arpit S.
Secure, Flexible Analytics Platform for SQL, ML, AI, and Geospatial
Reviewed on May 15, 2026
Review provided by G2
What do you like best about the product?
It supports various analytic types (SQL, ML, AI , geospatial) on a single platform. And it has deployment flexibility. One other thing I like is that it is secure.
What do you dislike about the product?
It is expensive as compared to other competitors. It is a bit complex and challenging for new users, not much user friendly. The user interface is very outdated.
What problems is the product solving and how is that benefiting you?
As a business analyst I use it to run SQL queries to extract insights from huge datasets. I also use it in building reports and dashboards. It also helps me to analyse customer behaviour, sales trends, or operational performance.
Balkishan N.
Strong Performance for Enterprise Data Warehousing
Reviewed on May 15, 2026
Review provided by G2
What do you like best about the product?
Teradata Vantage offers efficient distributed query processing, strong parallel performance, and reliable handling of large enterprise datasets across hybrid cloud environments.
What do you dislike about the product?
Initial setup, administration, and optimization can be complex, and troubleshooting sometimes requires deep platform expertise. Some workflows also feel less flexible compared to newer cloud-native analytics platforms.
What problems is the product solving and how is that benefiting you?
Teradata Vantage solves large-scale data warehousing and analytics challenges by providing high-performance parallel processing, centralized data management, and scalable analytics capabilities across hybrid environments. This improves query performance, operational efficiency, and business insights.
Lucky G.
Efficient for Large Data, Needs UX Improvements
Reviewed on May 14, 2026
Review provided by G2
What do you like best about the product?
I like Teradata Vantage's ability to handle very large datasets efficiently without major performance issues. It processes complex queries quickly, making reporting and analysis much more reliable and efficient. We also use it with reporting tools like Power BI and integrate it with our cloud storage, which has been quite useful.
What do you dislike about the product?
I believe one area could be the overall UX and ease of use as it can be difficult for new users. Specific aspects would be query optimization, navigation and understanding how different tools work together. The UX is not as intuitive.
What problems is the product solving and how is that benefiting you?
I use Teradata Vantage for data warehousing and analytics. It handles very large datasets efficiently and processes complex queries quickly, making reporting and analysis reliable and efficient.
Abhinav T.
Centralized Data Source, Handles Workloads Well but Rough Learning Curve
Reviewed on May 13, 2026
Review provided by G2
What do you like best about the product?
I like that Teradata Vantage solves the concurrent problem well. We have a lot of people using it simultaneously, with analysts running ad-hoc queries, dashboards refreshing, and ETL jobs running in the background. The workload management handles all of that without things falling over. It also provides one place where all our data lives, which has helped a lot with everyone having a 'single source of truth.'
What do you dislike about the product?
Learning curve is rough. Like, if you are new to Teradata you are gonna write queries that run forever and you won't know why, and then someone senior is gonna look at it and go 'your primary index is wrong' or 'you've got skew'. Also, the tools feel old.
What problems is the product solving and how is that benefiting you?
Teradata Vantage centralizes our data, providing one source of truth and streamlining decision-making. It also efficiently manages concurrent workloads, accommodating many users and processes simultaneously without issues.
Aditya A.
Unifies Legacy and New Data Streams Seamlessly
Reviewed on May 13, 2026
Review provided by G2
What do you like best about the product?
The advantage we get is that we have multiple systems or DB's which are legacy and some are new. Vantage helps us unify all their data stream into one
What do you dislike about the product?
Some legacy softwares are incomaptible with Vantage. This causes some issues with us either mnaually adding this data in our pipeline or using a mapper function
What problems is the product solving and how is that benefiting you?
As mentioned earlier since our org is little old we have multiple DB's from older generations and/or legacy systems which we are still utilizing. Vantage is helping us unify their data stream into one along with pulling in streams from newer systems.