I truly appreciate the unified lakehouse feature of IBM watsonx.data, as it allows me to keep all types of data in a single platform, which significantly simplifies analytics and eliminates the hassle of juggling multiple tools. I love the cost-efficient queries; being able to choose the best engine for the workload helps to reduce compute costs and boosts performance, which is a major asset. The strong governance capability is another aspect I value greatly, as it provides centralized access control and data cataloging. This ensures that data remains secure, compliant, and trusted—qualities crucial for enterprise environments. Additionally, the easy access to data across both cloud and on-premises systems without needing to relocate it is incredibly time-saving and reduces the effort required for data queries. Overall, these features make IBM watsonx.data an invaluable resource for managing and analyzing enterprise data. Review collected by and hosted on G2.com.

Setting up IBM watsonx.data can be complex, requiring skilled expertise, which creates a barrier for new users. The user interface has a learning curve and needs refinement to be more user-friendly. While integration works well with IBM tools, it needs improvement for non-IBM ecosystems, particularly in supporting multi-cloud systems, which can slow down adoption for organizations using diverse technological environments. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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 Review collected by and hosted on G2.com.

What I like most about IBM watsonx.data is that it brings different types of data into one place in a clean and organized way. The interface is simple to understand, so it didn’t take me long to get comfortable using it. It also handles larger datasets quite well, which is useful when working on analytics or reporting tasks.

I also appreciate that it comes with helpful features around governance and access control. Setting up permissions is easy, and it feels well integrated with other IBM tools, so I don’t have to jump between platforms. Overall, it makes daily data work smoother. Review collected by and hosted on G2.com.

The main thing I don’t like is that the initial setup takes some time, especially for someone not familiar with IBM’s overall environment. A few parts need multiple configuration steps, and I had to go through the documentation several times to understand how certain features worked.

Customer support is helpful, but sometimes the documentation could be clearer, which would reduce the need to contact support in the first place. Once everything is set up, though, the system works steadily without much trouble. Review collected by and hosted on G2.com.

I enjoy how IBM watsonx.data lets me access all my information from a single spot, regardless of where it's saved across various setups. It handles both organized and unstructured data smoothly, allowing for fast operations and cost savings while enabling me to uncover answers more quickly. I also appreciate its smooth AI integration and strong governance features that keep my data secure and well-managed. Furthermore, it provides a unified environment where I can use SQL, analytics, and AI tools together, simplifying work processes for different teams. The platform's support for federated queries makes analyzing data faster without the need for heavy ETL processes, and its ability to handle complex and messy data alongside clean tables under one roof is highly beneficial. Review collected by and hosted on G2.com.

Some aspects of IBM watsonx.data could be improved. Initially, it's challenging to navigate due to a steep learning curve, and the layout can be overwhelming for beginners. Integrating it with certain external applications requires more steps than necessary, which could be streamlined. A cleaner design and smoother setup process would facilitate easier adoption for new users. Review collected by and hosted on G2.com.

I really appreciate the capabilities of IBM watsonx.data in supporting my recent project, particularly for creating a function to change the localhost to an IP address on a local machine. This tools adds to my confidence and allows me to explore and gain deep knowledge on specific topics and points relevant to my coding needs. I find it incredibly valuable for running complex concepts and generating PDFs on a Linux server, which is highly beneficial for my project requirements. The integration simplicity particularly stands out for me, as it's very easy to integrate, especially when using AI agents. It supports creating chatbots or AIAgents seamlessly, which expands my ability to implement AI solutions efficiently. Review collected by and hosted on G2.com.

I faced a challenge with the key generator during the initial setup of IBM watsonx.data, which made the setup process difficult. Review collected by and hosted on G2.com.

I like that IBM watsonx.data is fast and easy to use. It allows me to store all my data in one place and execute quick queries, which is essential for managing large datasets. I appreciate its seamless integration with AI and analytics tools, simplifying my workflow. The platform helps me manage big data efficiently, reducing my struggles with slow queries and messy data. I value how it works well with cloud storage and BI tools like Power BI and Tableau, facilitating organized data visualization in BI dashboards. The initial setup was relatively smooth, aided by comprehensive documentation, which made the transition hassle-free. Review collected by and hosted on G2.com.

Sometimes the platform feels heavy when switching between different tools or views. A few advanced features take extra clicks to reach, and I think the UI could be more streamlined. Also, integrations outside the IBM ecosystem could be a bit smoother. Review collected by and hosted on G2.com.

I like the intuitive user interface of IBM watsonx.data, as it makes the setup process fairly easy and minimizes the need to overthink due to its well-organized layout. The UI placement is very thoughtful, ensuring that I can navigate the software without having to search around or get confused about where things are. This ease of use and intuitive design are significant benefits when working with data structuring, as I use IBM watsonx.data for normal factoring of data. Overall, the product's UI stands out as a highly positive aspect that contributes to a streamlined and efficient user experience. Review collected by and hosted on G2.com.

I find there is a significant delay in the response time, which can be frustrating. Additionally, IBM watsonx.data sometimes encounters issues with my proxy server, causing it to get blocked, which disrupts my workflow. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

This platform is extremely flexible and cost-effective. It combines the adaptability of a data lake with the high performance of a data warehouse. Additionally, it offers built-in support for multiple engines tailored to different workloads. Review collected by and hosted on G2.com.

It is still relatively new and lacks the maturity found in platforms like Snowflake and Databricks. The user interface is not very polished and can be slow at times. Additionally, the setup process can occasionally be complex. Review collected by and hosted on G2.com.