BigQuery vs IBM Db2 Warehouse on Cloud comparison

Google and IBM are both solutions in the Cloud Data Warehouse category. Google is ranked #3 with an average rating of 8.3, while IBM is ranked #16 with an average rating of 8.0. Google holds a 6.8% 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 41 BigQuery reviews

2,915 Views
1,576 Comparison Views

100% willing to recommend

IBM Db2 Warehouse on Cloud

Read 7 IBM Db2 Warehouse on Cloud reviews

144 Views
85 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: June 2025).

Buyer's Guide

BigQuery vs. IBM Db2 Warehouse on Cloud

June 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

3rd

Average Rating

8.2

Reviews Sentiment

7.2

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 June 2025, in the Cloud Data Warehouse category, the mindshare of BigQuery is 6.8%, down from 8.3% 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

Luís Silva

Chief Technical Lead at Human Code

Handles large data sets efficiently and offers flexible data management capabilities

The features I find most valuable in this solution are the ability to run and handle large data sets in a very efficient way with multiple types of data, relational as SQL data. It is kind of difficult to explain, but structured data and the ability to handle large data sets are key features. The data integration capabilities in BigQuery were, in fact, an issue at the beginning. There are two types of integrations. As long as integration is within Google, it is pretty simple. When you start to try to connect external clients to that data, it becomes more complex. It is not related to BigQuery, it is related to Google security model, which is not easy to manage. I would not call it an integration issue of BigQuery, I would call it an integration issue of Google security model.

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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

"The most valuable aspect of BigQuery is its ability to handle high data workloads without causing friction with our online systems."

"The feature called calibrating the capacity is valuable."

"The most valuable features of BigQuery is that it supports standard SQL and provides good performance."

"BigQuery excels at data analysis. It processes vast amounts of information using its advanced architecture and sophisticated querying capabilities, making it crucial for critical insights and safe for handling sensitive data."

"The product is serverless. We only need to write SQL queries to analyze the data. We need to pay based on the number of queries. The retrieval time is very less. Even if you write large queries, the tool is able to bring back data in a few seconds."

"BigQuery processes a substantial amount of data, whether in gigabytes or terabytes, swiftly producing desired data within one or two minutes."

"BigQuery's querying capabilities are very optimized for large datasets."

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

More BigQuery pros

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

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

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

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

Cons

"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 product’s performance could be much faster."

"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."

"I would like to see version-based implementation and a fallback arrangement for data stored in BigQuery storage. These are some features I'm interested in."

"The solution hinges on Google patterns so continued improvement is important."

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

"It would be beneficial to integrate additional tools, particularly from a business intelligence perspective."

"There is a good amount of documentation out there, but they're consistently making changes to the platform, and, like, their literature hasn't been updated on some plans."

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."

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

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

"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."

Pricing and Cost Advice

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

"I have tried my own setup using my Gmail ID, and I think it had a $300 limit for free for a new user. That's what Google is offering, and we can register and create a project."

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

"One terabyte of data costs $20 to $22 per month for storage on BigQuery and $25 on Snowflake. Snowflake is costlier for one terabyte, but BigQuery charges based on how much data is inserted into the tables. BigQuery charges you based on the amount of data that you handle and not the time in which you handle it. This is why the pricing models are different and it becomes a key consideration in the decision of which platform to use."

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

"The tool has competitive pricing."

"BigQuery is inexpensive."

"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."

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

16%

Financial Services Firm

16%

Manufacturing Company

12%

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?

I believe the cost of BigQuery is competitive versus the alternatives in the market, but it can become expensive if the tool is not used properly. It is on a per-consumption basis, the billing, so ...

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What needs improvement with BigQuery?

I have not used BigQuery for AI and machine learning projects myself. I know how to use it, and I can see where it would be useful, but so far, in my projects, I have not included a BigQuery compon...

See all answers

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 18% of the time

Oracle Autonomous Data Warehouse vs BigQuery

Compared 17% of the time

Teradata vs BigQuery

Compared 16% of the time

OpenText Analytics Database (Vertica) vs BigQuery

Compared 15% of the time

Apache Hadoop vs BigQuery

Compared 8% of the time

More BigQuery Competitors

Oracle Exadata vs IBM Db2 Warehouse on Cloud

Compared 35% of the time

IBM Netezza Performance Server vs IBM Db2 Warehouse on Cloud

Compared 33% of the time

Amazon Redshift vs IBM Db2 Warehouse on Cloud

Compared 31% of the time

More IBM Db2 Warehouse on Cloud Competitors

Product Reports

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BigQuery

June 2025

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Buyer's Guide

Cloud Data Warehouse

June 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

June 2025

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