BigQuery vs IBM Db2 Warehouse comparison

"Its integration with other tools like Atlan through a Google Chrome extension is highly beneficial."

"The feature called calibrating the capacity is valuable."

"The query tool is scalable and allows for petabytes of data."

"What I like most about BigQuery is that it's fast and flexible. Another advantage of BigQuery is that it's easy to learn."

"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."

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

"The most valuable features of this solution, in my opinion, are speed and performance, as well as cost-effectiveness."

"BigQuery can be used for any type of company. It has the capability of building applications and storing data. It can be used for OLTP or OLAP. It has many other products within the Google space."

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

"The solution is stable."

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

"Provides good security and reliability."

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

"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."

"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."

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

"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."

"An area for improvement in BigQuery is its UI because it's not working very well. Pricing for the solution is also very high."

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

"It can be slower and more problematic compared to other platforms such as Snowflake."

"When I execute a query, the dashboard doesn't always present the output seamlessly."

"Some of the queries are complex and difficult to understand."

"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."

"There is a limitation when copying data directly from BigQuery; it only supports up to ten MB when copying data to the clipboard."

"The primary challenges customers face with IBM Db2 Warehouse are related to its complexity in usage. It requires highly skilled professionals who understand Db2, and both training and support are challenging to obtain."

"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."

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

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

"Responding to support tickets takes a lot of time. It can range from two to four days, even for critical issues."

"IBM Db2 Warehouse needs to improve its interface."

"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 platform is inexpensive."

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

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

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

"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 product’s pricing could be more flexible for end users."

"The tool has competitive pricing."

"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."

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