IBM Cloud Pak for Data vs Rivery comparison

IBM and Rivery are both solutions in the Data Integration category. IBM is ranked #16 with an average rating of 8.2, while Rivery is ranked #34 with an average rating of 8.0. IBM holds a 1.8% mindshare in DI, compared to Rivery’s 0.3% mindshare. Additionally, 86% of IBM users are willing to recommend the solution, compared to 100% of Rivery users who would recommend it.

IBM Cloud Pak for Data

Read 13 IBM Cloud Pak for Data reviews

2,778 Views
1,932 Comparison Views

86% willing to recommend

Rivery

Read 2 Rivery reviews

301 Views
217 Comparison Views

100% willing to recommend

IBM Cloud Pak for Data

Rivery

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Executive SummaryUpdated on Dec 19, 2024

IBM Cloud Pak for Data and Rivery compete in the data management solutions category. Rivery seems to have the upper hand due to its agility and efficient deployment, appealing to those prioritizing flexibility.

Features: IBM Cloud Pak for Data offers comprehensive integration with AI and machine learning tools, focusing on data governance and security. Rivery provides a no-code interface and strong data pipeline automation, enhancing adaptability through operation simplicity.

Ease of Deployment and Customer Service: IBM Cloud Pak for Data generally requires a more complex setup suitable for detailed customization, backed by a sophisticated customer support framework. Rivery stands out with quick deployment and an intuitive setup, offering proactive customer service.

Pricing and ROI: IBM Cloud Pak for Data may involve higher initial setup costs but targets long-term ROI with deep integration capabilities. Rivery features a simpler pricing model, more affordable initial costs, and offers a higher ROI over shorter periods, making it appealing for budget-conscious businesses.

To learn more, read our detailed IBM Cloud Pak for Data vs. Rivery Report (Updated: April 2025).

Buyer's Guide

IBM Cloud Pak for Data vs. Rivery

April 2025

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

IBM Cloud Pak for Data

Ranking in Data Integration

16th

Average Rating

7.8

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Data Virtualization (3rd)

Rivery

Ranking in Data Integration

34th

Average Rating

8.6

Reviews Sentiment

7.3

Number of Reviews

Ranking in other categories

Migration Tools (4th), Cloud Migration (13th), Cloud Data Integration (19th)

Mindshare comparison

As of April 2025, in the Data Integration category, the mindshare of IBM Cloud Pak for Data is 1.8%, up from 1.7% compared to the previous year. The mindshare of Rivery is 0.3%, up from 0.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

Michelle Leslie

Data asset management engineer at a tech services company with 1-10 employees

Starts strong with data management capabilities but needs a demo database

What I would love to see is an end-to-end, almost a training demo database of some sort, where one of the biggest problems with data management is demonstrated. There are so many components to data management, and more often than not, people understand one thing really well. They may understand DataStage and how to move data around, but they do not see the impact of moving data incorrectly. They also do not see the impact of everyone understanding a piece of data in the same way. I would love Cloud Pak to come with a demo database that illustrates the different components of data management in a logical way, so I can see the whole picture instead of just the area I'm specializing in. It would be great if Cloud Pak, from a data modeling point of view, allowed us to import our PDMs, for example. It would be ideal to import and create business terms in Cloud Pak. The PEA would be great to create the technical data. The association between the business and the technical metadata could then be automated by pulling it through from your ACE models. The data modeling component is available in Cloud Pak. Additionally, when it comes to Cloud Pak, even though it has the NextGen DataStage built into it, there is Cloud Pak for data integration as well. Currently, I do not think we have a full enough understanding of how CP4D and CP4I can enhance each other.

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reviewer2335923

Senior Operations Analyst at a computer software company with 201-500 employees

Provides users with an initial setup phase, which is fairly simple to manage

I don't know what could be improved in terms of what my company was used to previously or after moving over to Rivery. I have not had much experience with platforms other than Rivery. For me, Rivalry was a way to step up from what we used. To be honest, I am not really sure what improvements could be made in Rivery. Pricing is a little steep for smaller organizations, I would say. The product's pricing model could be a little bit better. I am not aware if there are additional packages for smaller organizations, but if there are no packages available, then maybe that would be a good way to introduce something new in the tool.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"Scalability-wise, I rate the solution a nine or ten out of ten."

"DataStage allows me to connect to different data sources."

"I love the way that I can start at a very basic level with my data management journey by capturing my policies, justifying my data, and putting them into different categories to say this is data relating to individuals, for example, or data relating to geography."

"Cloud Pak's most valuable features are IBM MQ, IBM App Connect, IBM API Connect, and ISPF."

"One of Cloud Pak's best features is the Watson Knowledge Catalog, which helps you implement data governance."

"Cloud Pak is a very, very, very good system."

"The most valuable feature of IBM Cloud Pak for Data is the Modeler flows. The ability to develop models using a graphical approach and the capability to connect to various sources, as well as the data virtualization capabilities, allow me to easily access and utilize data that is dispersed across different sources."

"The most valuable features of IBM Cloud Pak for Data are the Watson Studio, where we can initiate more groups and write code. Additionally, Watson Machine Learning is available with many other services, such as APIs which you can plug the machine learning models."

More IBM Cloud Pak for Data pros

"The solution's most valuable features are that it is quick to connect and simple to use."

"Connects to many APIs in the market and new ones are being added all the time."

Cons

"The technical support could be a little better."

"The solution's user experience is an area that has room for improvement."

"One thing that bugs me is how much infrastructure Cloud Pak requires for the initial deployment. It doesn't allow you to start small. The smallest permitted deployment is too big. It's a huge problem that prevents us from implementing the solution in many scenarios."

"The interface could improve because sometimes it becomes slow. Sometimes there is a delay between clicks when using the software, which can make the development process slow. It can take a few seconds to complete one action, and then a few more seconds to do the next one."

"The solution's catalog searching or map search needs to be improved."

"Cloud Pak would be improved with integration with cloud service providers like Cloudera."

"There is a solution that is part of IBM Cloud Pak for Data called Watson OpenScale. It is used to monitor the deployed models for the quality and fairness of the results. This is one area that needs a lot of improvement."

"The product must improve its performance."

More IBM Cloud Pak for Data cons

"Lineage and an impact analysis or logic dependency are lacking."

"Pricing is a little steep for smaller organizations, I would say. The product's pricing model could be a little bit better."

Pricing and Cost Advice

"For the licensing of the solution, there is a yearly payment that needs to be made. Also, since it is expensive, cost-wise, I rate the solution an eight or nine out of ten."

"It's quite expensive."

"I think that this product is too expensive for smaller companies."

"IBM Cloud Pak for Data is expensive. If we include the training time and the machine learning, it's expensive. The cost of the execution is more reasonable."

"The solution's pricing is competitive with that of other vendors."

"The solution is expensive."

"Cloud Pak's cost is a little high."

"I don't have the exact licensing cost for IBM Cloud Pak for Data, as my company is still finalizing requirements, including monthly, yearly, and three-year licensing fees. Still, on a scale of one to five, I'd rate it a three because, compared to other vendors, it's more complicated."

"I rate the tool's price as six out of ten if I consider the lowest price to be one and the highest price to be ten."

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Top Industries

By visitors reading reviews

Financial Services Firm

27%

Computer Software Company

12%

Manufacturing Company

10%

Government

Financial Services Firm

17%

Computer Software Company

12%

Manufacturing Company

10%

Government

10%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about IBM Cloud Pak for Data?

DataStage allows me to connect to different data sources.

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What is your experience regarding pricing and costs for IBM Cloud Pak for Data?

The setup cost is very expensive. The cost depends on the pieces of the solution I'm using, how much data I have, and whether it's on the cloud or on-prem.

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What needs improvement with IBM Cloud Pak for Data?

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What is your experience regarding pricing and costs for Rivery?

The tool's price can be a little steep for a small organization. I rate the tool's price as six out of ten if I consider the lowest price to be one and the highest price to be ten.

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What needs improvement with Rivery?

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What is your primary use case for Rivery?

My company has started to use the Rivery extract data from Hive. It is like a project management sort of program, and we started to use Rivery to get the data from there over into Mavenlink, so we ...

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Comparisons

IBM InfoSphere DataStage vs IBM Cloud Pak for Data

Compared 42% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs IBM Cloud Pak for Data

Compared 18% of the time

Azure Data Factory vs IBM Cloud Pak for Data

Compared 12% of the time

Denodo vs IBM Cloud Pak for Data

Compared 11% of the time

Palantir Foundry vs IBM Cloud Pak for Data

Compared 8% of the time

More IBM Cloud Pak for Data Competitors

dbt vs Rivery

Compared 48% of the time

Azure Data Factory vs Rivery

Compared 35% of the time

Workato vs Rivery

Compared 17% of the time

More Rivery Competitors

Product Reports

Buyer's Guide

IBM Cloud Pak for Data

April 2025

Download IBM Cloud Pak for Data product report

Buyer's Guide

Data Integration

March 2025

Download Rivery product report

Also Known As

Cloud Pak for Data

No data available

Overview

IBM Cloud Pak® for Data is a fully-integrated data and AI platform that modernizes how businesses collect, organize and analyze data to infuse AI throughout their organizations. Cloud-native by design, the platform unifies market-leading services spanning the entire analytics lifecycle. From data management, DataOps, governance, business analytics and automated AI, IBM Cloud Pak for Data helps eliminate the need for costly, and often competing, point solutions while providing the information architecture you need to implement AI successfully.

Building on the streamlined hybrid-cloud foundation of Red Hat® OpenShift®, IBM Cloud Pak for Data takes advantage of the underlying resource and infrastructure optimization and management. The solution fully supports multicloud environments such as Amazon Web Services (AWS), Azure, Google Cloud, IBM Cloud™ and private cloud deployments. Find out how IBM Cloud Pak for Data can lower your total cost of ownership and accelerate innovation.

IBM

Rivery is a serverless, SaaS DataOps platform that empowers companies of all sizes around the world to consolidate, orchestrate, and manage internal and external data sources with ease and efficiency.

By offering comprehensive data solutions and partnering with complementary technology providers, including Google, Snowflake, Tableau, and Looker, Rivery enables data-driven companies to build the perfect ecosystems for all their data processes.

Rivery

Sample Customers

Qatar Development Bank, GuideWell, Skanderborg Music Festival

Information Not Available

Buyer's Guide

IBM Cloud Pak for Data vs. Rivery

April 2025

Free Report: IBM Cloud Pak for Data vs. Rivery

Find out what your peers are saying about IBM Cloud Pak for Data vs. Rivery and other solutions. Updated: April 2025.

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