IBM Watson Studio enables users to build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio enables users can operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. The vendor states the solution simplifies AI lifecycle management and accelerates time to value with an open, flexible multicloud architecture.
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Teradata Vantage
Score 8.1 out of 10
N/A
Teradata Vantage is presented as a modern analytics cloud platform that unifies everything—data lakes, data warehouses, analytics, and new data sources and types. Supports hybrid multi-cloud environments and priced for flexibility, Vantage delivers unlimited intelligence to build the future of business.
Users can deploy Vantage on public clouds (such as AWS, Azure, and GCP), hybrid multi-cloud environments, on-premises with Teradata IntelliFlex, or on commodity hardware with VMware.
$4,800
per month
Pricing
IBM Watson Studio on Cloud Pak for Data
Teradata Vantage
Editions & Modules
No answers on this topic
Teradata VantageCloud Lake
from $4800
per month
Teradata VantageCloud Enterprise
from $9000
per month
Offerings
Pricing Offerings
IBM Watson Studio
Teradata Vantage
Free Trial
No
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
Optional
Additional Details
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More Pricing Information
Community Pulse
IBM Watson Studio on Cloud Pak for Data
Teradata Vantage
Features
IBM Watson Studio on Cloud Pak for Data
Teradata Vantage
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
IBM Watson Studio on Cloud Pak for Data
8.1
22 Ratings
3% below category average
Teradata Vantage
-
Ratings
Connect to Multiple Data Sources
8.022 Ratings
00 Ratings
Extend Existing Data Sources
8.022 Ratings
00 Ratings
Automatic Data Format Detection
10.021 Ratings
00 Ratings
MDM Integration
6.414 Ratings
00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
IBM Watson Studio on Cloud Pak for Data
10.0
22 Ratings
17% above category average
Teradata Vantage
-
Ratings
Visualization
10.022 Ratings
00 Ratings
Interactive Data Analysis
10.022 Ratings
00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
IBM Watson Studio on Cloud Pak for Data
9.5
22 Ratings
15% above category average
Teradata Vantage
-
Ratings
Interactive Data Cleaning and Enrichment
10.022 Ratings
00 Ratings
Data Transformations
10.021 Ratings
00 Ratings
Data Encryption
8.020 Ratings
00 Ratings
Built-in Processors
10.021 Ratings
00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
IBM Watson Studio on Cloud Pak for Data
9.5
22 Ratings
12% above category average
Teradata Vantage
-
Ratings
Multiple Model Development Languages and Tools
10.021 Ratings
00 Ratings
Automated Machine Learning
10.022 Ratings
00 Ratings
Single platform for multiple model development
10.022 Ratings
00 Ratings
Self-Service Model Delivery
8.020 Ratings
00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
It has a lot of features that are good for teams working on large-scale projects and continuously developing and reiterating their data project models. Really helpful when dealing with large data. It is a kind of one-stop solution for all data science tasks like visualization, cleaning, analyzing data, and developing models but small teams might find a lot of features unuseful.
Teradata Vantage is well suited for large scale ETL pipelines like the ones we developed for anti money laundering risk matrices. It handles heavy joins, aggregations, and transformations on transactional data efficiently. We generate alert variables, adjust for inflation, and monitor establishments monthly with it, all integrated with Python and Control-M for a centralised automation across the company. For less appropriate, I would say that heavy resource demands might slow down experimentation for iterative work.
Teradata is an excellent option but only for a massive amount of data warehousing or analysis. If your data is not that big then it could be a misfit for your company and cost you a lot. The cost associated is quite extensive as compared to some other alternative RDBMS systems available in the market.
Migration of data from Teradata to some other RDBMS systems is quite painful as the transition is not that smooth and you need to follow many steps and even if one of them fails. You need to start from the beginning almost.
Last but not least the UI is pretty outdated and needs a revamp. Though it is simple, it needs to be presented in a much better way and more advanced options need to bee presented on the front page itself.
Teradata is a mature RDBMS system that expands its functionality towards the current cloud capabilities like object storage and flexible compute scale.
Teradata Vantage allows us to create a scalable infrastructure to support our strategic initiatives. The dedicated compute power ensures reliable performance with isolated workloads and dedicated resources, optimizing workflows for faster, more efficient data transfers. The compute clusters support ETL processes and OSF’s developers and data science team with the flexibility to create self-service analytics, to spin up/down at any time, driving better performance and minimizing costs.
I received answers mostly at once and got answered even further my question: they gave me interesting points of view and suggestion for deepening in the learning path
We have meetings at the beginning with the technical team to explain our requirements to them and they were really putting in a lot of effort to come up with a solution which will address all our needs. They implemented the software and also trained a few of our resources on the same too. We can get in touch with them now as well whenever we run into a roadblock but it's very less now.
The main reason I personally changed over from Azure ML Studio is because it lacked any support for significant custom modelling with packages and services such as TensorFlow, scikit-learn, Microsoft Cognitive Toolkit and Spark ML. IBM Watson Studio provides these services and does so in a well integrated and easy to use fashion making it a preferable service over the other services that I have personally used.
Teradata is way ahead of its competitor because of its unique features of ensuring data privacy and data never gets corrupted even in worst case scenario. In most cases, the data corruption is a major issue if left unused and it leads to important data being wiped off which in ideal case should be stored for 3 years
Moving to Teradata in the Cloud-enabled a level of agility that previously didn't exist in the organization. It also enabled a level of analytic competency that was not achievable using other options on the aggressive timeline that was required. We didn't want to settle for reinventing a wheel when we had a super tuned performance capable beast readily available in Teradata. Teradata lets us focus on our business rather than spending money and effort trying to design software or database foundations features on an open source or lower performance platform.