BigQuery vs IBM Db2 Warehouse comparison

Google and IBM are both solutions in the Cloud Data Warehouse category. Additionally, 100% of Google users are willing to recommend the solution, compared to 81% of IBM users who would recommend it.

BigQuery

Read 44 BigQuery reviews

5,305 Views
4,403 Comparison Views

100% willing to recommend

IBM Db2 Warehouse

Read 12 IBM Db2 Warehouse reviews

2,550 Views
2,015 Comparison Views

81% willing to recommend

BigQuery

IBM Db2 Warehouse

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Executive Summary

We performed a comparison between BigQuery and IBM Db2 Warehouse based on real PeerSpot user reviews.

Find out what your peers are saying about Snowflake Computing, Teradata, Google and others in Cloud Data Warehouse.

To learn more, read our detailed Cloud Data Warehouse Report (Updated: July 2026).

Buyer's Guide

Cloud Data Warehouse

July 2026

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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

Average Rating

8.2

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (3rd)

IBM Db2 Warehouse

Average Rating

7.8

Reviews Sentiment

6.1

Number of Reviews

Ranking in other categories

Data Warehouse (13th)

Featured Reviews

Mikah Sellers

Principal at Sgt Suds

Has supported detailed policy and education analysis with low-code data exploration

I do not use AWS as my main cloud provider within the company and am not currently using it with AWS. My company did not buy it through the AWS Marketplace as I'm the founder of the company. I do not use BigQuery's integration with Google Analytics for custom behavior analysis. I have not utilized the geospatial analysis capabilities with BigQuery as I'm doing mostly human capital work, so geospatial wouldn't make sense. I would rate their service on a scale of one to 10 for Google as ten. I would rate BigQuery as nine out of 10. My experience with the pricing for BigQuery was through a grant from Google. Their pricing is fairly priced and pretty comparable to Microsoft's offering. I haven't had direct experience, but I did look at the pricing of the Microsoft offering and it's pretty similar. I do not deal with Google AI tools such as Vertex.

Read full review

Sherpard Muzuva

Senior Technical Manager at SYSTEMS INTEGRATED LTD (SYMPHONY)

Advanced features enhance business intelligence, but complex management calls for improved user guidance

While my experience with IBM Db2 Warehouse is somewhat limited, when compared to other databases such as Oracle, there are areas for improvement. They need to enhance the database to make it more user-friendly and easier to master. They should implement a more comprehensive graphical user interface with additional features. For instance, when users encounter problems, the system should provide better guidelines and troubleshooting directions, except for hardware-related issues. They need to implement tools that would help users perform basic troubleshooting rather than solely relying on support. Other databases have features where users can investigate specific issues using error codes. From my experience, many minor issues could be resolved before escalating to support.

Read full review

Quotes from Members

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

Pros

"It's straightforward to set up."

"The solution's reporting, dashboard, and out-of-the-box capabilities match exactly our requirements."

"It is stable and reliable; there are no bugs or glitches."

"I like that we can synch and run a large query. I also like that we can work with a large amount of data. You don't need to work separately, as it's a ready-made solution. It also comes with a built-in machine-learning feature. Once we start inputting the data, it will suggest some things related to the data, and we can come up with nice dashboards and statistics from a vast amount of data."

"BigQuery allows for very fast access, and it is efficient in handling large datasets compared to other SQL databases."

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

"There are some performance features like partitioning, which you can do based on an integer, and it improves the performance a lot."

"The main thing I like about BigQuery is storage. We did an on-premise BigQuery migration with trillions of records. Usually, we have to deal with insufficient storage on-premises, but in BigQuery, we don't get that because it's like cloud storage, and we can have any number of records. That is one advantage. The next major advantage is the column length. We have some limits on column length on-premises, like 10,000, and we have to design it based on that. However, with BigQuery, we don't need to design the column length at all. It will expand or shrink based on the records it's getting. I can give you a real-life example based on our migration from on-premises to GCP. There was a dimension table with a general number of records, and when we queried that on-premises, like in Apache Spark or Teradata, it took around half an hour to get those records. In BigQuery, it was instant. As it's very fast, you can get it in two or three minutes. That was very helpful for our engineers. Usually, we have to run a query on-premises and go for a break while waiting for that query to give us the results. It's not the case with BigQuery because it instantly provides results when we run it. So, that makes the work fast, it helps a lot, and it helps save a lot of time. It also has a reasonable performance rate and smart tuning. Suppose we need to perform some joins, BigQuery has a smart tuning option, and it'll tune itself and tell us the best way a query can be done in the backend. To be frank, the performance, reliability, and everything else have improved, even the downtime. Usually, on-premise servers have some downtime, but as BigQuery is multiregional, we have storage in three different locations. So, downtime is also not getting impacted. For example, if the Atlantic ocean location has some downtime, or the server is down, we can use data that is stored in Africa or somewhere else. We have three or four storage locations, and that's the main advantage."

More BigQuery pros

"The solution is stable."

"IBM Db2 Warehouse is more resilient when dealing with business intelligence applications."

"It's easy and practical to use."

"It can be mounted on the cloud, which is a huge plus. If the client, for example, starts small with on-premise deployment and then it rapidly needs to grow, we can transfer this to the cloud easily."

"The solution works with big data, so it's pretty scalable."

"Some of the best features are stored procedures, parallelism, and different indexing strategies."

"The analytics engine is not bad at forecasting predictions."

"I think it scales really well and as long as you take enough time to learn a little bit about it, it works really well."

More IBM Db2 Warehouse pros

Cons

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

"It would be beneficial if BigQuery could be made more affordable."

"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."

"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."

"Sometimes, support specialists might not have enough experience or business understanding, which can be an issue."

"The initial setup could be improved making it easier to deploy."

"BigQuery can be very expensive if not used properly. Introducing AI tools that would allow you to optimize the data extraction process is an area of serious improvement."

More BigQuery cons

"There should be more material available for training and training should be free."

"The biggest problems we have is when the backup solution is failing or slow and we run out of log space, which has happened probably a couple of times in the last four years."

"The biggest challenge anyone could have with Db2 Warehouse is their references or online resources and documentation. They are very, very, very limited on the web."

"Lacks sufficient documentation and particularly in Spanish."

"There were some initial challenges with IBM Db2 Warehouse about eight months ago when I worked in this environment. When I coordinated with IBM support, they mentioned that the memory was insufficient for our needs. Our business environment required significantly more memory than the previous cluster could provide. Consequently, we have worked closely with on-site IBM technical personnel to address this issue."

"The areas of the solution that is needing the most improvement are separating compute from storage, elasticity, which means scaling up and then retracting."

"IBM Db2 Warehouse needs to improve its interface."

"I previously used DataStage, which I think is better than InfoSphere Warehouse."

More IBM Db2 Warehouse cons

Pricing and Cost Advice

"Price-wise, I think that is very reasonable."

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

"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 tool has competitive pricing."

"BigQuery pricing can increase quickly. It's a high-priced solution."

"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."

"The pricing is adaptable, ensuring that organizations can tailor their usage and costs based on their specific requirements and configurations within the Google Cloud Platform."

"The product operates on a pay-for-use model. Costs include storage and query execution, which can accumulate based on data volume and complexity."

More BigQuery pricing and cost advice

"In a traditional on-prem database, in a data warehouse, the solution is probably on the expensive side."

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Top Industries

By visitors reading reviews

Financial Services Firm

16%

Outsourcing Company

11%

Media Company

10%

Manufacturing Company

Financial Services Firm

24%

Construction Company

11%

Comms Service Provider

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	15
Midsize Enterprise	10
Large Enterprise	19

By reviewers
Company Size	Count
Small Business	5
Midsize Enterprise	3
Large Enterprise	5

Questions from the Community

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 ...

See all answers

What needs improvement with BigQuery?

The queries that BigQuery provides are not optimized at a greater level. For simple tasks it is good, but if I want to write complex analyzing queries, it doesn't give the queries up to the mark, s...

See all answers

What is your primary use case for BigQuery?

My main use case for BigQuery is the analysis of our data, creating dashboards from large datasets, and querying the databases that we have, including both structured and unstructured data imported...

See all answers

What is your experience regarding pricing and costs for IBM Db2 Warehouse?

The pricing for medium and large environments is almost the same as Oracle. I rate the pricing as six out of ten.

See all answers

What needs improvement with IBM Db2 Warehouse?

See all answers

What is your primary use case for IBM Db2 Warehouse?

The main advantages of IBM Db2 Warehouse become apparent when dealing with business intelligence applications. I worked with it when it was installed for one of our customers, a utilities company, ...

See all answers

Comparisons

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Compared 7% of the time

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Compared 5% of the time

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Compared 10% of the time

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Compared 8% of the time

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Compared 8% of the time

Magnitude vs IBM Db2 Warehouse

Compared 7% of the time

IBM Netezza Performance Server vs IBM Db2 Warehouse

Compared 4% of the time

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Product Reports

Buyer's Guide

BigQuery

August 2026

Download BigQuery product report

Buyer's Guide

IBM Db2 Warehouse

July 2026

Download IBM Db2 Warehouse product report

Also Known As

InfoSphere Warehouse, IBM InfoSphere Warehouse

Overview

BigQuery is a powerful cloud-based data warehouse offering advanced SQL querying, seamless Google integration, and scalable handling of large datasets. Its serverless architecture and built-in AI capabilities facilitate efficient data processing and insights extraction.

BigQuery provides an efficient data analysis platform with low-latency performance and cost-effective on-demand pricing. Leveraging Google's cloud infrastructure for data storage, it offers robust security and high availability. While it excels in SQL support and caching features, it can improve on user accessibility, integration with diverse tools, and machine learning feature expansion. Making it more accessible for smaller entities through improved cost management and local data compliance is essential. Enhancements in query speed and intuitive interfaces can further optimize performance.

What features are offered by BigQuery?

User-friendly interface: Simplifies data interaction, making complex processes more manageable.
Serverless architecture: Eliminates the need for infrastructure management, improving scalability and efficiency.
Advanced SQL querying: Enables complex data retrieval and manipulation with ease.
Machine learning integration: Facilitates AI-driven insights directly from the platform.
Cost-effective pricing: On-demand pricing helps manage expenses by paying only for used resources.
Seamless Google integration: Works well with familiar Google services for a cohesive experience.
High availability and robust security: Ensures data is secure and accessible when needed.

What benefits should be considered when evaluating BigQuery?

Efficient data processing: Quickly handles large datasets, supporting fast data-driven decision-making.
Scalable infrastructure: Grows capacity alongside business needs without manual infrastructure adjustments.
Enhanced data analysis: SQL support and caching features improve analysis precision and speed.
AI and machine learning capabilities: Enable advanced data insights and predictive analytics.
Integration with existing tools: Ensures smooth workflow transitions with services such as Google Analytics and Tableau.

In industries like healthcare, finance, and marketing, BigQuery is extensively used for data storage, generating reports, and supporting ETL processes. Educational institutions leverage it for analytics, aligning seamlessly with Google Cloud for serverless infrastructure efficiencies.

Google

IBM Db2 Warehouse provides scalable and efficient data handling, offering rapid data processing, excellent integration capabilities, and strong security. Its compatibility with cloud environments and robust analytics make it ideal for enterprises requiring high-performance transaction processing.

IBM Db2 Warehouse is recognized for its big data scalability and fast response times. Its support for ETL processes and robust security measures ensures consistent data handling. Easy installation and a powerful analytics engine facilitate forecasting, making it practical for high-volume transactions. It supports Windows and Linux, offering a flexible yet resilient environment. However, improvements are needed in separating compute from storage, interface usability, and Spanish documentation. Users may experience delays in support response and challenges with publication and backup issues, highlighting the need for enhanced training resources and user-friendly troubleshooting tools. Though related to Oracle, IBM Db2 Warehouse may benefit from improved user guidance and online resources.

What are the standout features of IBM Db2 Warehouse?

Scalability: Effectively handles big data volumes.
Integration: Seamlessly works with multiple platforms, including IBM Cognos.
Analytics Engine: Robust tools support forecasting and advanced analytics.
Security: Offers strong security measures for data protection.
Cloud Compatibility: Deployable on IBM Cloud with ease.

What benefits and ROI should users consider?

Data Processing Speed: Fast response boosts efficiency.
Reliability: High volume transactions are managed efficiently.
Analytics Power: Enhances decision-making with data analytics capabilities.
Deployment Flexibility: Supports Windows and Linux systems.

IBM Db2 Warehouse is implemented across industries for data warehousing, reporting, and analytics, notably benefiting businesses focusing on utilities usage prediction and growth analysis. Its integration with IBM Cognos enhances report generation, while its support for star or snowflake schemas optimizes high-volume data management, providing a solid foundation for data-driven decision-making in business intelligence applications.

IBM

Sample Customers

Information Not Available

Alameda County Social Services Agency, Sui Southern Gas Company Limited

Find out what your peers are saying about Snowflake Computing, Teradata, Google and others in Cloud Data Warehouse. Updated: July 2026.

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