BigQuery vs IBM Db2 Warehouse on Cloud comparison

Google and IBM are both solutions in the Cloud Data Warehouse category. Google is ranked #4 with an average rating of 8.3, while IBM is ranked #16 with an average rating of 8.0. Google holds a 7.0% mindshare in CDW, compared to IBM’s 0.5% mindshare. Additionally, 100% of Google users are willing to recommend the solution, compared to 85% of IBM users who would recommend it.

BigQuery

Read 40 BigQuery reviews

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2,698 Comparison Views

100% willing to recommend

IBM Db2 Warehouse on Cloud

Read 7 IBM Db2 Warehouse on Cloud reviews

145 Views
113 Comparison Views

85% willing to recommend

BigQuery

IBM Db2 Warehouse on Cloud

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Executive SummaryUpdated on Dec 18, 2024

IBM Db2 Warehouse on Cloud and BigQuery compete in the cloud data warehousing category. While IBM Db2 Warehouse on Cloud offers robust integration and security features, BigQuery is often preferred for its superior analytics capabilities and scalability despite potential cost considerations.

Features: IBM Db2 Warehouse on Cloud excels in integration with IBM systems, encryption, and a user-friendly management console. BigQuery stands out with its serverless architecture, scalable data processing, and seamless integration with other Google Cloud services.

Room for Improvement: IBM Db2 Warehouse on Cloud could enhance its analytics speed and lower long-term costs. Improving user interface and cloud-native features could also be beneficial. BigQuery could focus on reducing complexity for non-technical users, simplifying cost management, and expanding real-time analytics features.

Ease of Deployment and Customer Service: IBM Db2 Warehouse on Cloud is known for its easy deployment within IBM ecosystems and reliable support. BigQuery offers a streamlined setup in Google Cloud environments, enhanced by efficient customer service, benefiting from its cloud-native design.

Pricing and ROI: IBM Db2 Warehouse on Cloud provides competitive initial setup costs and reasonable ROI within IBM infrastructures. BigQuery might be more expensive initially but offers significant long-term ROI through its powerful features and pay-as-you-go pricing model.

To learn more, read our detailed BigQuery vs. IBM Db2 Warehouse on Cloud Report (Updated: April 2025).

Buyer's Guide

BigQuery vs. IBM Db2 Warehouse on Cloud

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

BigQuery

Ranking in Cloud Data Warehouse

4th

Average Rating

8.2

Reviews Sentiment

7.3

Number of Reviews

Ranking in other categories

No ranking in other categories

IBM Db2 Warehouse on Cloud

Ranking in Cloud Data Warehouse

16th

Average Rating

7.6

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of May 2025, in the Cloud Data Warehouse category, the mindshare of BigQuery is 7.0%, down from 8.2% compared to the previous year. The mindshare of IBM Db2 Warehouse on Cloud is 0.5%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse

Featured Reviews

VikashKumar1

Tech lead at Ford Motor Company

Easy to maintain and provides high availability

Since I used BigQuery over the GCP cloud environment, I'm not sure whether we can go through internal IDEAs like IntelliJ or DBeaver that we use to connect with databases. Instead of connecting directly to BigQuery, we connect to GCP, Cloud Run, and then to BigQuery, which is a long process. Sometimes, we face some issues, bugs, and defects. We must first connect with a VPN to check data issues while working from home. Then, it allows you to connect to the cloud. After logging into the cloud, it searches for the service we are looking for, and then we go to BigQuery. This is a long process. After that, we analyze the issues in a table. Instead, it would be very helpful if it could provide a tool that we can install on our MacBook or Windows system. Once we open this tool, we can connect directly to the BigQuery server and easily perform tasks.

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FarhanFarhan

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…

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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

"It has a well-structured suite of complimentary tools for data integration and so forth."

"The initial setup is simple."

"The product's most valuable features include its scalability and the ability to handle complex queries on large datasets."

"One of the most significant advantages lies in the decoupling of storage and compute which allows to independently scale storage and compute resources, with the added benefit of extremely cost-effective storage akin to object storage solutions."

"The initial setup is straightforward."

"It's similar to a Hadoop cluster, except it's managed by Google."

"Even non-coders can review the data in BigQuery."

"BigQuery has a very nice interface that you can easily learn if you know SQL."

More BigQuery pros

"It is stable when there is support from IBM."

"It will be MPP, so performance should improve."

"The performance is okay as long as the volume of queries is not too high."

"The way that it scales will help a lot of customers that are stuck with Netezza boxes that can't grow any larger."

Cons

"There are some limitations in the query latency compared to what it was three years ago."

"We'd like to have more integrations with other technologies."

"There are many tools that you have to use with BigQuery that are different services also provided for by Google. They need to all be integrated into BigQuery to make the solution easier to use."

"It would be helpful if they could provide some dashboards where you can easily view charts and information."

"As a product, BigQuery still requires a lot of maturity to accommodate other use cases and to be widely acceptable across other organizations."

"When it comes to queries or the code being executed in the data warehouse, the management of this code, like integration with the GitHub repository or the GitLab repository, is kind of complicated, and it's not so direct."

"The process of migrating from Datastore to BigQuery should be improved."

"It would be better if BigQuery didn't have huge restrictions. For example, when we migrate from on-premises to on-premise, the data which handles all ebook characters can be handled on-premise. But in BigQuery, we have huge restrictions. If we have some symbols, like a hash or other special characters, it won't accept them. Not in all cases, but it won't accept a few special characters, and when we migrate, we get errors. We need to use Regexp or something similar to replace that with another character. This isn't expected from a high-range technology like BigQuery. It has to adapt all products. For instance, if we have a TV Showroom, the TV symbol will be there in the shop name. Teradata and Apache Spark accept this, but BigQuery won't. This is the primary concern that we had. In the next release, it would be better if the query on the external table also had cache. Right now, we are using a GCS bucket, and in the native table, we have cache. For example, if we query the same table, it won't cost because it will try to fetch the records from the cached result. But when we run queries on the external table a number of times, it won't be cached. That's a major drawback of BigQuery. Only the native table has the cache option, and the external table doesn't. If there is an option to have an external table for cache purposes, it'll be a significant advantage for our organization."

More BigQuery cons

"Ultimately, the product itself has challenges and we are not currently satisfied with the support, either."

"There are some limitations in adding data files to table spaces, and improvements are needed for regional support."

"Right now, we are implementing on ESX VMware 6.0. Support for this platform is poor. Also, one of the backup/recovery options is broken and IBM is not addressing the issue."

"Containers get corrupted very easily. Restoring them using GPFS can result in a lot of issues."

"Tech support for dashDB is awful. We usually have tickets open for three to four weeks."

Pricing and Cost Advice

"The platform is inexpensive."

"The pricing appears to be competitive for the intended usage scenarios we have in mind."

"We are above the free threshold, so we are paying around 40 euros per month for BigQuery."

"1 TB is free of cost monthly. If you use more than 1 TB a month, then you need to pay 5 dollars extra for each TB."

"The pricing is good and there are no additional costs involved."

"The solution is pretty affordable and quite cheap in comparison to PDP or Cloudera."

"The tool has competitive pricing."

"Its cost structure operates on a pay-as-you-go model."

More BigQuery pricing and cost advice

"If your going to go with warehouse DB/dashDB, use the cloud or Sailfish version."

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Top Industries

By visitors reading reviews

Computer Software Company

17%

Financial Services Firm

15%

Manufacturing Company

11%

Retailer

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about BigQuery?

The initial setup process is easy.

See all answers

What is your experience regarding pricing and costs for BigQuery?

The price is perceived as expensive, rated at eight out of ten in terms of costliness. Still, it offers significant cost savings.

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What needs improvement with BigQuery?

When I open many of the Google Cloud products, I am in an environment that I do not feel familiar with; it is a little overwhelming. In general, if I know SQL and start playing around, it will star...

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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...

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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.

See all answers

What is your primary use case for IBM Db2 Warehouse on Cloud?

Our primary use case is data storage and analytics.

See all answers

Comparisons

Snowflake vs BigQuery

Compared 21% of the time

Oracle Autonomous Data Warehouse vs BigQuery

Compared 17% of the time

Teradata vs BigQuery

Compared 16% of the time

Vertica vs BigQuery

Compared 14% of the time

Apache Hadoop vs BigQuery

Compared 8% of the time

More BigQuery Competitors

Oracle Exadata vs IBM Db2 Warehouse on Cloud

Compared 34% of the time

IBM Netezza Performance Server vs IBM Db2 Warehouse on Cloud

Compared 34% of the time

Amazon Redshift vs IBM Db2 Warehouse on Cloud

Compared 32% of the time

More IBM Db2 Warehouse on Cloud Competitors

Product Reports

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BigQuery

April 2025

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Cloud Data Warehouse

April 2025

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Also Known As

No data available

IBM dashDB

Overview

BigQuery is an enterprise data warehouse that solves this problem by enabling super-fast SQL queries using the processing power of Google's infrastructure. ... You can control access to both the project and your data based on your business needs, such as giving others the ability to view or query your data.

Google

IBM dashDB family offers private and public cloud database solutions for transactional and analytic workloads, with IBM fully managed or client managed options with a Common SQL engine across all deployment options.

IBM

Sample Customers

Information Not Available

Copenhagen Business School, BPM Northwest, GameStop

Buyer's Guide

BigQuery vs. IBM Db2 Warehouse on Cloud

April 2025

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