BigQuery vs IBM Db2 Warehouse comparison

"As a cloud solution, it's easy to set up."

"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 BigQuery is that it supports standard SQL and provides good performance."

"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."

"It's straightforward to set up."

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

"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."

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

"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."

"It can scale effectively as long as resources are available."

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

"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."

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

"The solution is stable."

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

"Provides good security and reliability."

"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."

"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."

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

"The solution should reduce its pricing."

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

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

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

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

"IBM Db2 Warehouse needs to improve its interface."

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

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

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

"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 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 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."

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

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

"The solution's pricing is cheaper compared to other solutions."

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

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

"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."

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

"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."

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