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IBM Db2 Warehouse on Cloud vs OpenText Analytics Database (Vertica) comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Mar 29, 2026

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 Db2 Warehouse on Cloud
Ranking in Cloud Data Warehouse
16th
Average Rating
7.6
Reviews Sentiment
6.3
Number of Reviews
7
Ranking in other categories
No ranking in other categories
OpenText Analytics Database...
Ranking in Cloud Data Warehouse
11th
Average Rating
8.2
Reviews Sentiment
6.9
Number of Reviews
90
Ranking in other categories
Data Warehouse (6th)
 

Mindshare comparison

As of October 2026, in the Cloud Data Warehouse category, the mindshare of IBM Db2 Warehouse on Cloud is 2.1%, up from 0.8% compared to the previous year. The mindshare of OpenText Analytics Database (Vertica) is 5.1%, down from 6.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Mindshare Distribution
ProductMindshare (%)
OpenText Analytics Database (Vertica)5.1%
IBM Db2 Warehouse on Cloud2.1%
Other92.8%
Cloud Data Warehouse
 

Featured Reviews

FM
Database Engineer at Meezan Bank
Enhancing analytics with seamless data dumping and reliable support
Our primary use case is data storage and analytics The organization has decided to purchase a full stack solution from IBM due to positive responses, which helped them upgrade from the previous version. The data dumping into the raw zone and the feature of BigQuery is quite attractive. There…
JN
consultant at tcs
Data warehousing has transformed reporting performance and now delivers near real-time insights
OpenText Analytics Database (Vertica) is a very powerful analytic database, but like any platform, there are areas where it can improve to make daily work even smoother. Better cloud-native experience is one area for improvement. OpenText Analytics Database (Vertica) was originally designed as an on-premises analytic database and later moved to cloud. Improvement opportunities include more seamless cloud-native features such as auto-scaling, serverless options, and easier cluster management. Competitors such as Snowflake and BigQuery provide more fully managed experiences. Easier UI is another area for improvement. Most administration is currently done by SQL and command line tools. An improvement opportunity would be a more modern web UI for monitoring, workload management, and troubleshooting. Faster ecosystem and community growth is needed. In short, OpenText Analytics Database (Vertica) could improve in areas such as cloud-native capability, modern UI for administration, stronger real-time streaming integration, and growing its ecosystem and community. These enhancements would make it easier to manage and adopt compared to newer cloud-first analytic platforms. From a day-to-day operational perspective, there are a few areas where OpenText Analytics Database (Vertica) could improve to make our work smoother. Smarter automatic projection management is needed with more intelligence, auto projection creation, automatic optimization, and reduced manual testing with better workload management. Right now, monitoring queries often requires system tables and manual analysis. Troubleshooting slow queries takes time. A modern real-time dashboard showing query bottlenecks and resource users would enable quick detection. The impact could be faster issue resolution and less time spent debugging performance. Storage native interaction with modern data tools is also important. In short, from a day-to-day perspective, improvements in automatic projection optimization, better workload monitoring dashboard, easier schema evolution, and stronger modern tool integration would significantly reduce manual tuning effort and improve developer productivity. While OpenText Analytics Database (Vertica) is very powerful, these enhancements would make it more efficient for the analytics team.

Quotes from Members

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

Pros

"The way that it scales will help a lot of customers that are stuck with Netezza boxes that can't grow any larger.​"
"DashDB is a good product to work with and the extra cost you spend on performance, technical support and tools to work with is worth it."
"One of the most amazing features of dashDB is how it uses compression to get results in lighting speed."
"Since my company is an IBM partner, it has enabled us to offer cloud data warehouse solutions on a 100% IBM stack."
"It will be MPP, so performance should improve."
"Ease of migration from Netezza DB; IBM ported over all Netezza's functionality and made the warehouse DB/dashDB the best of breed of the two."
"It is stable when there is support from IBM."
"I like that the dashDB solution is built on DB2 technology, which means that you can use all the features of a DB2 database while outsourcing all the hardware and software maintenance."
"The hardware usage and speed has been the most valuable feature of this solution, as it is very fast and has saved us a lot of money."
"OpenText Analytics Database (Vertica) has improved our reporting performance by nearly 90 percent, reduced ETL processing time by more than half, and saved around 70 percent in storage through compression."
"I appreciate the flexibility offered by Vertica's projections. It allows for modifying the primary projection without altering the tables, which helps to optimize queries without the need to modify the underlying data."
"Scalability has been amazing; we have seen a lot of improvement and can describe our clusters by petabytes and scale them by the number of users, with one project having 15 to 20 consecutive users dealing with petabytes of storage."
"The most valuable feature is the merge function, which is essentially the upsert function, and it has become our ELT pattern because, unlike when we used the ETL tool to manage upserts, the load time is now pretty much flat relative to the volume of records processed."
"Its projections and encoding are excellent tools for tuning large volumes."
"Customer Service: Excellent! Technical Support: Excellent!"
"Before Vertica, we used a combination of sharded RDBMSs and Hive: the typical runtime for a query was in the hours; it's now in the seconds, with way more data than then (we're talking hundreds of terabytes)."
 

Cons

"The support channels need to improve."
"Ultimately, the product itself has challenges and we are not currently satisfied with the support, either."
"I would like to see improvements in backup and authentication. It needs the ability to increase the number of retained backups to more than 2 days."
"Tech support for dashDB is awful. We usually have tickets open for three to four weeks."
"Db2 is not a solution that I recommend. We have a lot of experience and we are not satisfied with the product or the support that we received."
"Containers get corrupted very easily. Restoring them using GPFS can result in a lot of issues."
"I would rate the level of dashDB support 3.5/5. While they are very knowledgeable in many areas, you can still struggle to get the correct resolution."
"There are some limitations in adding data files to table spaces, and improvements are needed for regional support."
"Improve Vertica logging and messages to Vertica startup commands."
"Sometimes users write bad queries that has brought down the cluster."
"It should provide a GUI interface for data management and tuning."
"The product could improve by adding support for a wider variety of data types and enhancing features to better compete with other databases."
"Whatever is out, the core is not always as great as the engine, especially their first version."
"vbr.py needs to be improve to support diff no of nodes source to target."
"There have been some issues with deleting and updating data from tables."
"Machine learning implementations."
 

Pricing and Cost Advice

"If your going to go with warehouse DB/dashDB, use the cloud or Sailfish version."
"Read the fine print carefully."
"The solution is relatively cost-effective."
"It's an expensive product"
"The pricing and licensing depend on the size of your environment and the zone where you want to implement."
"The pricing depends on the license model because there are several. It depends on the client, but it's cheaper than other solutions. I think it's cheap for all the functionality and robustness. It's not very expensive to deploy."
"Work with a vendor, if possible, and take advantage of more aggressive discounts at mid-fiscal year (April) and fiscal year-end (October).​"
"I think it's starting to get a little expensive. Open source products are starting to get more robust, so I think that's something that they need to start looking at in terms of licensing."
"It is fast to purchase through the AWS Marketplace."
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Comms Service Provider
12%
Construction Company
9%
Outsourcing Company
9%
Financial Services Firm
16%
Outsourcing Company
13%
Manufacturing Company
10%
Comms Service Provider
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business4
Large Enterprise3
By reviewers
Company SizeCount
Small Business29
Midsize Enterprise23
Large Enterprise43
 

Questions from the Community

What advice do you have for others considering IBM Db2 Warehouse on Cloud?
Organizations of all sizes, especially those who are in need of powerful and elastic cloud data warehouse solutions that can help administrators maximize the efficiency of their data-based operatio...
What needs improvement with IBM Db2 Warehouse on Cloud?
There are some limitations in adding data files to table spaces, and improvements are needed for regional support.
What is your primary use case for IBM Db2 Warehouse on Cloud?
Our primary use case is data storage and analytics.
What is your experience regarding pricing and costs for Vertica?
My experience with pricing, setup cost, and licensing is limited because the organization handled the licensing and pricing as well as the cost setup.
What needs improvement with Vertica?
OpenText Analytics Database (Vertica) is already doing great. There could be a community which could have been much more advanced and more people can be engaged so that any kind of questions, queri...
What is your primary use case for Vertica?
The main use case for OpenText Analytics Database (Vertica) is that we have the Hive and a Hadoop layer for data availability, and Vertica serves as a big data solution. Within a Hive table, OpenTe...
 

Also Known As

IBM dashDB
Micro Focus Vertica, HPE Vertica, HPE Vertica on Demand
 

Overview

 

Sample Customers

Copenhagen Business School, BPM Northwest, GameStop
Cerner, Game Show Network Game, Guess by Marciano, Supercell, Etsy, Nascar, Empirix, adMarketplace, and Cardlytics.
Find out what your peers are saying about IBM Db2 Warehouse on Cloud vs. OpenText Analytics Database (Vertica) and other solutions. Updated: October 2026.
917,403 professionals have used our research since 2012.