IBM watsonx.data as a Service
IBM SoftwareExternal reviews
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Great tool to support our future
What do you like best about the product?
it gives a view into data at an enterprise level
What do you dislike about the product?
a little clunky especially at the beginning. not very intuitive either.
What problems is the product solving and how is that benefiting you?
Accelerate growth and speed to market with new product offerings
Great tool for our future
What do you like best about the product?
When paired correctly it can be very powerful
What do you dislike about the product?
At first use it's a bit clunky and didn't give us what we really expected
What problems is the product solving and how is that benefiting you?
We want to use it to identified structured and unstructured documents easily and get their data.
WatsonX.data review
What do you like best about the product?
Integration with all variety of data bases
What do you dislike about the product?
Still exploring, will find more as our organization use it more
What problems is the product solving and how is that benefiting you?
Generating data insights
watsonx.data review
What do you like best about the product?
that we can use the milvus database and that it connects easily to the rest of the ibm services.
What do you dislike about the product?
Milvus: milvus admin permissions suck a little, whoever makes it has total control and access is totally seperate from rest of account permissions.
What problems is the product solving and how is that benefiting you?
Solving the problem of holding our data for our project.
Data Ingestion
What do you like best about the product?
Architecturally watsonx.data is best where you could add as many as catalogs and federation has been made easy. access control makes a big difference so does the multi engines like presto,spark,db2warehouse etc.
What do you dislike about the product?
I wish the integration part is tightly attached to watsonx.data UI in order to run jobs directly from watsonx.data UI rather than going into other services like integration and run job from there.I found many issues with Presto c++ when inserting the data , i dont know if that is limitation:
Limited File Format Support
Restricted Table Creation
Syntax & Compatibility Issues
Catalog Limitations
Data Ingestion Challenges:Can't load CSV directly into tables using code:
Presto/Trino vs Other Technologies:
Feature Presto/Trino Spark SQL Databricks
DML Operations ❌ Limited ✅ Full ✅ Full
CSV Support ❌ Limited ✅ Full ✅ Full
Delta Lake ❌ No ✅ Yes ✅ Native
Table Creation ❌ Restricted ✅ Full ✅ Full
Data Ingestion ❌ Complex ✅ Easy ✅ Easy
Limited File Format Support
Restricted Table Creation
Syntax & Compatibility Issues
Catalog Limitations
Data Ingestion Challenges:Can't load CSV directly into tables using code:
Presto/Trino vs Other Technologies:
Feature Presto/Trino Spark SQL Databricks
DML Operations ❌ Limited ✅ Full ✅ Full
CSV Support ❌ Limited ✅ Full ✅ Full
Delta Lake ❌ No ✅ Yes ✅ Native
Table Creation ❌ Restricted ✅ Full ✅ Full
Data Ingestion ❌ Complex ✅ Easy ✅ Easy
What problems is the product solving and how is that benefiting you?
IBM watsonx.data solved the data silos
Reliable
What do you like best about the product?
What I really like about IBM watsonx.data is its ability to handle and analyze large amounts of structured and unstructured data from different sources all in one place. It’s flexible, integrates well with existing tools, and helps turn raw data into meaningful insights much faster. I also appreciate how it’s built for scalability, so it can grow with the business needs
What do you dislike about the product?
One thing I’ve noticed is that, because IBM watsonx.data is such a powerful and feature-rich platform, there can be a learning curve for new users to fully leverage all its capabilities. Also, depending on the size of the datasets and complexity of queries, performance tuning might be needed to get the best results. But once you get familiar with it, the benefits outweigh the initial challenges
What problems is the product solving and how is that benefiting you?
IBM watsonx.data is solving the problem of having data scattered across multiple systems and formats. Instead of spending a lot of time moving and preparing data, I can query and analyze it directly from where it resides, whether it’s in a data lake, warehouse, or external source. This saves time, reduces duplication, and makes it easier to get real-time insights for decision-making. It’s also helping improve collaboration, since different teams can work off the same unified view of the data
Data as a service, i think this is something fresh and new
What do you like best about the product?
The reason i explored IBM watsonx is, in my current org, we were also building a similiar kind of product, not at this scale but many of the funcitonalitier are common, the feature i liked specially is their prompt lab and how well it is easy to implement, and that actually provides a very good simulation for building different kinds of usecases a person may have. in terms of integration, the data source integration feels seemless a wide variety mainstream connectors are present and easy to integrate, didnt ineracted with the customer support as i didnt have to use it much
What do you dislike about the product?
This not a beginner friendly tool, a person should be well aware of the current AI-scenario, technical terms and how LLMS works upto some level, the UI is clean and minimal but many time i found a bit of difficulty in navigation between different screens, and sometimes i felt everything is given to me, and that made me confused what should i pick, the point is since there is big chunk of business and non-tech professionals are also adopting the use of LLMs into their workflows, and they could be a user of this platfrom, then the platform should hide some of the configuration and handle it via some assumptions, although this is just an opinion i am not very sure of the target audiene of watsonx. for my use i dont see much of use within my team, and current org, there are already many tools which are free and opensource for instance openmetadata, people who want production ready and readiness to scale within their org as they have that much data to take leverage, and exclusive proprietary platform, which is catered for them then this could be a good choice.
What problems is the product solving and how is that benefiting you?
the first is its proprietary nature with ease of integration with my data, that will help organization to quickly bootstrap their products, next is the fine tuning and its simulation with prompt labs, this will actually gives the user an idea how his model will behave without wasting much of his resources on billing and computing,
Review for Open House Leak House
What do you like best about the product?
I'm very impressed about the flexibilty it offers as Apache Iceberg and multiple query engines.
The Way is it being deisgned for handling the AI data for application.
The Feature of Data Governance & Quality Management
The Way is it being deisgned for handling the AI data for application.
The Feature of Data Governance & Quality Management
What do you dislike about the product?
Complicated to Adoption, big learning curve
Integration not that open, seems less capable.
Integration not that open, seems less capable.
What problems is the product solving and how is that benefiting you?
It makes data more meaningful to us & we can use that data for analysis, which further leads to AI Capabilities .
Good AI Platform
What do you like best about the product?
enables highly customizable conversational AI across multiple channels like websites, mobile apps, WhatsApp, and Slack, supporting consistent user experiences .
What do you dislike about the product?
Looks like fre more enhancement can be performed such as on result driven and response.
What problems is the product solving and how is that benefiting you?
transforming over 1 million data points per second into immersive fan experiences via AI-driven content and personalization demonstrating practical enterprise deployment .
Innovative model
What do you like best about the product?
It has inbuilt data lakes, tools for security purposes. It has everything combined in one place that saves time and efforts.
What do you dislike about the product?
It doesnt support with the other ecosystems like AWS. It has deep learning curve
What problems is the product solving and how is that benefiting you?
Solves the challenge of analyzing the data , storing it and processing it has been made very easy. It's an all in one platform and that's how it benefited me.
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