Sold by: IBM SoftwareÂ
Deployed on AWS
Built on a lakehouse architecture, IBM watsonx.data is an open, hybrid, and governed data store optimized for all data, analytics, and AI workloads.
Overview
IBM watsonx.data is an open, hybrid, and governed data store built on an open data lakehouse architecture. The data lakehouse is an emerging architecture that offers the flexibility of a data lake with the performance and structure of a data warehouse. Watsonx.data is an enterprise-ready data store that enables hybrid cloud analytics workloads such as data engineering, data science and business intelligence, through open-source components with integrated IBM innovation.
Watsonx.data will allow users to access their data through a single point of entry and run multiple fit-for-purpose query engines such as Presto and Spark across IT environments.With the integration of DataStax Astra DB, watsonx.data now extends beyond analytics to support real time operational workloads and advanced AI applications. Astra DB brings enterprise-grade vector database capabilities and multi-model data support, enabling organizations to build generative AI applications, real time recommendation engines, and high-performance operational systems,all within the same unified platform. This integration eliminates the need for separate operational databases and provides seamless data flow between transactional and analytical workloads. Through workload optimization an organization can reduce data warehouse costs by up to 50 percent by augmenting with this solution. It also offers built-in governance, automation and integrations with an organization's existing databases and tools to simplify setup and user experience.
Db2 Warehouse and Netezza on AWS natively integrate with watsonx.data with shared metadata and support for open formats such as Parquet and Iceberg to share and combine data for new insights without ETL. Watsonx.data allows customers to augment data warehouses such as Db2 Warehouse and Netezza and optimize workloads for performance and cost.
For trials and customized IBM watsonx.data pricing contact your IBM Sales Representative or email us at watsonx_on_AWS@wwpdl.vnet.ibm.com Visit https://www.ibm.com/products/watsonx-dataÂ
to learn more about our consumption model and product editions.
For more information on IBM watsonx.data visit https://www.ibm.com/products/watsonx-dataÂ
Highlights
- Access all your data across hybrid-cloud: Access all data through a single point of entry with a shared metadata layer across clouds and on-premises environments.
- Get started in minutes: Connect to storage and analytics environments in minutes and enhance trust in data with built-in governance, security, and automation.
- Reduce the cost of your data warehouse by up to 50% through workload optimization: Optimize costly data warehouse workloads across multiple query engines and storage tiers, pairing the right workload with the right engine.
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Deployed on AWS
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Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
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Dimension | Description | Cost/12 months |
|---|---|---|
Extra-small Watsonx.data installation | Watsonx.data Resource Units annual Contract "pack" of 2000 Resource Units | $2,000.00 |
Small Watsonx.data installation | Watsonx.data Resource Units annual Contract "pack" of 20000 Resource Units | $20,000.00 |
Medium Watsonx.data installation | Watsonx.data Resource Units annual Contract "pack" of 50000 Resource Units | $50,000.00 |
Large Watsonx.data installation | Watsonx.data Resource Units annual Contract "pack" of 100000 Resource Units | $100,000.00 |
Dimension | Cost/unit |
|---|---|
Overage charge for overconsumption of contracted resource units | $1.10 |
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All orders are non-cancellable and all fees and other amounts that you pay are non-refundable.
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Updated weekly
By IBM Software
By Databricks, Inc.
By Dremio
Top
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In Data Warehouses
Top
10
In Databases & Analytics Platforms, ML Solutions, Data Analytics
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In Data Warehouses
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
Data Lakehouse Architecture
Built on an open data lakehouse architecture that combines data lake flexibility with data warehouse performance and structure
Multi-Engine Query Support
Supports multiple fit-for-purpose query engines like Presto and Spark across different IT environments
Vector Database Integration
Integrates DataStax Astra DB for enterprise-grade vector database capabilities and multi-model data support
Open Format Compatibility
Natively supports open data formats like Parquet and Iceberg for seamless data sharing and combination
Hybrid Cloud Data Access
Enables unified data access through a single point of entry with a shared metadata layer across hybrid cloud environments
Data Platform Architecture
Unified platform integrating data engineering, analytics, business intelligence, data science, and machine learning on a single architecture
Open Source Foundation
Built on open source data projects with support for open standards and data formats
Lakehouse Infrastructure
Provides a common data management approach using a lakehouse architecture running on Amazon S3
Data Intelligence Engine
Advanced engine capable of interpreting organizational data context and enabling broad data access across teams
Collaborative Workflow
Native collaboration capabilities enabling cross-functional data and AI workflow integration
Data Lake Query Performance
Provides sub-second query response times using SQL query service on data lake platforms
Open Standards Support
Utilizes community-driven standards like Apache Iceberg and Apache Arrow for processing engines
Multi-Source Data Integration
Enables joining data from data lakes and external databases without data movement
Compute Engine Management
Automatically handles compute engine lifecycle including provisioning, scaling, pausing, and decommissioning
VPC-Based Data Processing
Deploys compute engines within customer's Amazon Virtual Private Cloud for secure data processing
Validated by AWS Marketplace
FedRAMP
GDPR
HIPAA
ISO/IEC 27001
PCI DSS
SOC 2 Type 2
No security profile
No security profile
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Standard contract
No
No
No
Customer reviews
3.5
1 ratings
1 AWS reviews
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82 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.
Madhav M.
User-Friendly Interface and Seamless Open-Source Integration
Reviewed on Nov 15, 2025
Review provided by G2
What do you like best about the product?
The user-friendly interface makes it easy to work with data, and the platform’s foundation on open-source software helps avoid vendor lock-in. This also allows for seamless integration with existing data stored in other cloud storage solutions, such as Azure Blob.
What do you dislike about the product?
The lack of support for JSON or multi-file inputs in batch deployment jobs is a significant drawback. Additionally, some data types, such as char and time, are not handled properly, and there are also restrictions on the maximum length allowed for varchar fields.
What problems is the product solving and how is that benefiting you?
We use multiple cloud providers, which has resulted in our data being fragmented across different cloud zones. This fragmentation makes it challenging to obtain a unified view of our data, and we are unable to rely on a single storage system because clients sometimes require us to use the cloud service they already have, such as data stored in azure blob or aws s3. watsonx data addresses this issue by providing a single point of entry to access all our data.
Information Technology and Services
Effortless Data Management and Seamless Integration in One Platform
Reviewed on Nov 15, 2025
Review provided by G2
What do you like best about the product?
What I appreciate most is how smoothly it manages large amounts of data without slowing down. Being able to connect various data sources, explore them, and run queries seamlessly is a big plus. I also value how everything is organized in a single platform—there’s no need to switch between multiple tools just to accomplish a straightforward task. This not only saves me time but also spares my patience. That’s really what made it stand out for me.
What do you dislike about the product?
The main drawback for me is the initial learning curve. If you’re not already familiar with IBM’s ecosystem, it can take some time to get a handle on how everything is organized—the setup, the integrations, and the governance layers all require some adjustment. Another issue is that certain features seem a bit too dispersed. At times, you have to navigate through several menus just to reach settings that should be easier to find. While this isn’t a deal-breaker, it does slow you down when you need to work quickly. Finally, although the platform generally performs well, I think the documentation could benefit from more real-world examples and guidance for edge cases. For enterprise-level tasks, those specifics are important. Overall, there’s nothing seriously negative, but these minor issues do create some friction for everyday users.
What problems is the product solving and how is that benefiting you?
The main challenge this solves for me is managing scattered data. Rather than switching between multiple storage systems and tools, watsonx.data provides a single platform where I can handle everything querying, governance, access control, and analytics. This consolidation alone saves significant time and helps minimize errors.
It also addresses performance concerns. Previously, running large queries across data from different sources was often slow or unreliable, but the engine here processes heavy workloads much more efficiently.
Governance is another area where I’ve seen improvement. Keeping track of who has access to which datasets and maintaining compliance is typically a complex task, but watsonx.data simplifies this with centralized policy management.
In summary, it reduces manual effort, keeps my data well-organized, and allows me to spend more time on analysis rather than constantly managing backend processes.
It also addresses performance concerns. Previously, running large queries across data from different sources was often slow or unreliable, but the engine here processes heavy workloads much more efficiently.
Governance is another area where I’ve seen improvement. Keeping track of who has access to which datasets and maintaining compliance is typically a complex task, but watsonx.data simplifies this with centralized policy management.
In summary, it reduces manual effort, keeps my data well-organized, and allows me to spend more time on analysis rather than constantly managing backend processes.
Hari N.
Efficient Platform with Room for Simplicity
Reviewed on Nov 15, 2025
Review provided by G2
What do you like best about the product?
I like how fast, flexible, and easy it makes managing and analyzing large datasets.
What do you dislike about the product?
Sometimes the interface feels a bit complex, especially when navigating advanced features.
What problems is the product solving and how is that benefiting you?
It helps me manage and analyze large datasets faster and more efficiently, which saves time and improves the accuracy of my insights.
Aman K.
Reliable Data Access with a Steep Learning Curve
Reviewed on Nov 15, 2025
Review provided by G2
What do you like best about the product?
I use IBM watsonx.data primarily for training my AI models, and it significantly aids me in my learning purposes. The standout feature for me is its reliability, which provides governed, high-performance, and consistent access to data across hybrid environments. The platform's ability to use open formats along with robust metadata management is a huge advantage. I appreciate that I can access data from anywhere in a very hassle-free manner, which solves a common problem for me because, in my experience, similar models tend to require a lot of information, making them ultimately unusable. These aspects make IBM watsonx.data an excellent tool for my requirements.
What do you dislike about the product?
I find that IBM watsonx.data could improve its ease of use. It has a steep learning curve which makes it less accessible for beginners. The user interface is not very intuitive, adding to the difficulty of using the software effectively. Setting up the application is complex unless you thoroughly understand the necessary steps. Moreover, there is limited seamless integration with non-IBM tools, which could hinder its use in environments that rely on diverse software solutions.
What problems is the product solving and how is that benefiting you?
I use IBM watsonx.data for training AI models. It solves access issues by enabling data access from anywhere with high performance and consistent data across environments, reducing the hassle compared to other models.
Urvish T.
Real-Time Data Analysis with Effortless Setup
Reviewed on Nov 15, 2025
Review provided by G2
What do you like best about the product?
I greatly appreciate IBM watsonx.data's real-time data analysis capabilities and robust storage. They are essential for handling data related to active user interactions, enabling me to generate real-time recommendations that enhance user experience. The platform effectively solves data streaming and storage issues for my applications, which focus on monitoring user behaviors and interactions with stories. The initial setup was straightforward, making it easy to create data flow pipelines, contributing to its user-friendly nature. Because of these features and overall performance, I find it to be a complete solution that meets my needs without the need to look elsewhere, rating it highly at 9.5 out of 10.
What do you dislike about the product?
I haven't used any other service, and I liked what I used
What problems is the product solving and how is that benefiting you?
I use IBM watsonx.data for data streaming, storage, and real-time analysis, which enhances user behavior insights and allows us to generate immediate recommendations.