BigQuery vs IBM Db2 Warehouse comparison

"We like the machine learning features and the high-performance database engine."

"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."

"We basically used it to store server data and generate reports for enterprise architects. It was a valuable tool for our enterprise design architect."

"It's pretty stable. It's fast, and it is able to go through large quantities of data pretty quickly."

"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."

"It has a proprietary way of storing and accessing data in its own data store and is 100% managed without you needing to install anything. There is no need to arrange for any infrastructure to be able to use this solution."

"This solution is highly scalable."

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

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

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

"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."

"Provides good security and reliability."

"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 most valuable features of IBM Db2 Warehouse include its availability, easy integration, ability to deal with a large size of data, excellent performance with no delays, powerful security mechanisms, and effective support."

"The standout feature of IBM Db2 Warehouse, which is particularly valuable for large enterprises, is its ability to handle big data."

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

"The processing capability can be an area of improvement."

"The price could be better. Compared to competing solutions, BigQuery is expensive. It's only suitable for enterprise customers, not small and medium-sized businesses, as they cannot afford this kind of solution. In the next release, it would be better if they improved their AI bot. Although machine learning and artificial intelligence are doing wonders, there is still a lot of room to enhance them."

"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."

"I understand that Snowflake has made some improvements on its end to further reduce costs, so I believe BigQuery can catch up."

"I rate BigQuery six out of 10 for affordability. It could be cheaper."

"I noticed recently it's more expensive now."

"They could enhance the platform's user accessibility."

"When I execute a query, the dashboard doesn't always present the output seamlessly. Troubleshooting requires opening each pipeline individually, which is time-consuming."

"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."

"In terms of improvement, IBM Db2 Warehouse should be more scalable."

"IBM Db2 Warehouse needs to improve its interface."

"It takes a long time to have a new version or release, similar to Oracle."

"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."

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

"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."

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

"BigQuery is inexpensive."

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

"The price could be better. Usually, you need to buy the license for a year. Whenever you want more, you can subscribe to it, and you can use it. Otherwise, you can terminate the license. You can use it daily or monthly, and we use it based on a project's requirements."

"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."

"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."

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

"The price is a bit high but the technology is worth it."

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